Python: Python 3.7 beginner
Technology:
Expertise:
- 11 Courses | 14h 1m 46s
- 10 Books | 62h
- 39 Courses | 20h 39m
- 10 Books | 46h 44m
- Includes Lab
- 6 Courses | 9h 40m 34s
- 8 Books | 41h 15m
- 1 Course | 1h 16m 54s
- 2 Courses | 2h 18m 8s
- 6 Courses | 7h 49m
- 5 Books | 34h 45m
- Includes Lab
- 5 Courses | 5h 52m 8s
- 8 Books | 24h 46m
- 12 Courses | 11h 47m 34s
- 10 Books | 69h 30m
- Includes Lab
- 11 Courses | 14h 21m 28s
- 5 Books | 25h 36m
- Includes Lab
- 4 Courses | 6h 16m 25s
- 6 Courses | 3h
- Includes Lab
- 2 Courses | 2h 54m 9s
- 1 Course | 1h 32m 19s
- 2 Courses | 3h 1m 5s
- 5 Courses | 6h 56s
- 5 Courses | 6h 9m 46s
- 2 Courses | 3h 40m 3s
Explore Python, the general purpose high-level programming language focused on code readability and efficiency.
GETTING STARTED
IT Infrastructure Automation: Python Automation Programming
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3m 5s
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7m 23s
GETTING STARTED
Python Development: Getting Started with Programming in Python
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2m 3s
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6m 17s
GETTING STARTED
Flask in Python: An Introduction to Web Frameworks & Flask
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2m 3s
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9m 13s
GETTING STARTED
Building Web Apps Using Django: Introduction to Web Frameworks & Django
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2m 2s
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8m 20s
GETTING STARTED
Excel with Python: Working with Excel Spreadsheets from Python
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2m 5s
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4m 9s
GETTING STARTED
Python Design Patterns: Principles of Good Design
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2m 11s
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6m 3s
GETTING STARTED
Web Applications with Django: Introducing the Django Web Framework
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2m 57s
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9m
GETTING STARTED
Flask in Python: User Interactions in Flask Applications
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2m 6s
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5m 32s
GETTING STARTED
Dash Python Framework: Dash for Interactive Web Apps
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2m 6s
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11m 3s
GETTING STARTED
Developing Apps with Tkinter: Getting Started
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2m 18s
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6m 8s
GETTING STARTED
Dash Python Framework: Leveraging Dash with User Input & Dash DataTable
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2m 19s
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10m 39s
COURSES INCLUDED
IT Infrastructure Automation: Python Automation Programming
Explore Python and how Python can be used to create and manage automation in an IT environment.
15 videos |
1h 36m
Assessment
Badge
Python - Introduction to Pandas and DataFrames
Simplify data analysis with Pandas DataFrames. Pandas is a Python library that enables you to work with series and tabular data, including initialization, and population. For this course, learners do not need prior experience working with Pandas, but should be familiar with Python3, and Jupyter Notebooks. Topics include the following: Define your own index for a Pandas series object; load data from a CSV (comma separated values) file, to create a Pandas DataFrame; Add and remove data from your Pandas DataFrame; Analyze a portion of your DataFrame; Examine how to reshape or reorient data, and to create a pivot table. Finally, represent multidimensional data in two-dimensional DataFrames, with multi or hierarchical indexes.
14 videos |
1h 4m
Assessment
Badge
Python - Manipulating & Analyzing Data in Pandas DataFrames
Explore advanced data manipulation and analysis with Pandas DataFrames, a Python library that shares similarities with relational databases. To take this course, prior basic experience is needed with Pandas DataFrames, data loading, and Jupyter Notebook data manipulation. You will learn to iterate data in your DataFrame. See how to export data to Excel files, JSON (JavaScript Object Notation) files, and CSV (comma separated values) files. Sort the contents of a DataFrame and manage missing data. Group data with a multi-index. Merge disparate data into a single DataFrame through join and concatenate operations. Finally, you will determine when and where to integrate data with structured queries, similar to SQL.
10 videos |
44m
Assessment
Badge
Conditional Statements & Loops: If-else Control Structures in Python
Learners will explore implementations of the order of precedence of operators, using if-elif-else statements to evaluate multiple conditions and conversions between various data types in Python, in this 15-video course. Key concepts covered here include how conditions in Python work, and how to evaluate conditions by involving primitive data types using if statements and complex data types using if statements. Next, evaluate multiple conditions for decision making with nested control structures; identify how to use the if-else statement to make decisions involving complex data types such as lists, tuples, and dictionaries; and learn how to convert an integer to a float and a float or an integer to a string, and vice-versa. Learners then observe how to convert primitive data types to complex data types, to convert between various complex data types, and to convert between various complex data types and view base conversions with Python built-in functions; and to solve various programming problems with Python built-in methods. Finally, you will learn to solve various programming problems by using if-elif-else statements and nested if-else statements.
15 videos |
1h 40m
Assessment
Badge
Conditional Statements & Loops: The Basics of for Loops in Python
Loops are one way to perform the same operations repeatedly in a program. For loops are the control structure to use when the repeated operations are performed on a sequence such as a list or a tuple. In this 9-video course, you will explore different ways to iterate over a sequence using for loops. Key concepts covered in this course include how to use for loops to process elements in a list and characters in a string; and how to code for loops to iterate over values in a tuple and the keys and values in a dictionary. Next, learn the function of associating an else block with a Python for loop; include if-else statements and other for loops within a for loop; how to generate a sequence of consecutive integers with the range function; and how to use the range function to iterate over a large range of values and apply it within nested for loops. Finally, observe how to write for loops in order to iterate over 1-dimensional and 2-dimensional sequences.
9 videos |
1h 1m
Assessment
Badge
Conditional Statements & Loops: Advanced Operations Using for Loops in Python
Explore how iterating over elements using for loops can be controlled using the break and continue statements in Python. Creating sequences from other sequences using comprehensions is also covered in this 9-video course. Key concepts covered here include how to terminate a for loop when a specific condition is met using the break statement; learning how the break statement affects the code in the else block of a for loop; and observing how to skip an iteration of a for loop when a specific condition is met using the continue statement. Next, learn how to use the continue statement along with the break statement within the same for loop; learn the fact that no action is performed under specific conditions by using the pass statement; and create a list out of the contents of another list using a comprehension. Finally, you will learn about conditions in list comprehensions in order to filter elements used in the source list and to define values in the newly created list.
9 videos |
1h 5m
Assessment
Badge
Conditional Statements & Loops: While Loops in Python
While loops are one way to keep repeating a set of actions until a specific condition is met in Python. In this 11-video course, learners explore the use of while loops, considerations when implementing while loops, and use cases for while loops and for loops. Key concepts covered here include implementing a basic while loop and recognizing what conditions cause it to become an infinite loop; learning to use while loops to carry out actions while evaluating expressions based on numerical and string data; and examining while loops whose iterations depend on user input data. Next, learn syntax for defining while loops within a single line; learn to iterate over a list of elements with while loops; and learn to iterate over multiple lists and tuples with while loops. Learn when it is appropriate to use break keyword to stop a while loop, and learn to break out of a while loop and recognize use of the pass keyword within such loops. Finally, learn skip steps in individual iterations of a while loop using the continue statement.
11 videos |
1h 19m
Assessment
Badge
Python Concurrent Programming: Introduction to Concurrent Programming
Explore the general theory of concurrent programming, and examine how to have multiple tasks active at any given point in time. This 14-video course offers an in-depth examination of concurrent programming by using the Python programming language. First, learners will examine the two main forms of concurrent programming, multithreading and multiprocessing, and examine their differences and use cases. Next, you will examine executing multitask sequentially, and with multithreading to save time, and how to use multiprocessing to manage a collection of tasks efficiently. Continue by exploring challenges that programmers encounter when adopting concurrency such as synchronization issues and deadlocks, and how to address these issues. You will examine issues that arise when writing concurrent code, and you will learn how to fix these by using the built-in objects available in Python. Finally, this course examines several of the objects available in the Python language such as queues and pools, which simplify the task of building multithreading and multiprocessing applications.
14 videos |
1h 29m
Assessment
Badge
Python Concurrent Programming: Multithreading in Python
This course offers an in-depth exploration of the creation and management of concurrent threads in Python. In its 14 videos, you will learn how to significantly improve the performance and responsiveness of your apps by using concurrent threads. Begin by examining how threads are created in Python from their initialization to their execution; then learn how to use the various synchronization mechanisms such as locks, semaphores, and events. Next, you will examine how concurrent execution could occur in two ways: multithreading and parallel. You will learn to use multithreading to run chunks of each task at one time, and then switch between them regularly. You will learn multiprocessing of threads by executing tasks in parallel. Learners will examine concurrent execution of threads, and some of the issues that arise when these threads are not synchronized. Finally, you will examine several threads of synchronization mechanisms available in Python such as locks, semaphores, events, and conditions and explore the properties and use cases for each of these objects.
14 videos |
1h 41m
Assessment
Badge
Python Concurrent Programming: Multiprocessing in Python
This course is a lab-only exploration of the creation and management of processes in Python to speed up the execution of your programs. In this 10-video course, learners will use Jupyter notebooks to execute all programs demonstrated. First, you will learn how to create initialized threads, and how to do the same with processes in Python. Then you will examine different thread-safe data structures in Python to implement queues, stacks, and priority queues. Next, you will learn how to use Python for synchronization mechanisms and inter-process communication, and will see a comparison of processes to threads. You will learn to use Python's built-in queue data structure for multithreaded applications, and how to implement multiprocessing. Continue by learning how processes are created and executed and how they differ from threads when one is using shared resources. You will explore how to use a manager class, or service process manager to share any Python types. Finally, you will examine the available mechanisms in Python for communication and synchronization between processes.
10 videos |
1h 16m
Assessment
Badge
Python Concurrent Programming: Asynchronous Executions in Python
This 9-video course offers a lab-only exploration and introduction to the libraries available in Python to run tasks asynchronously by using both processes and threads. To take this course, you should have prior knowledge of how to spawn and manage processes in Python. First, you will learn how to significantly improve the performance and responsiveness of your application by running them concurrently, then learn how to create a process pool, and how to use multiprocessing to execute tasks in parallel. Next, you will learn to use multithreading to run chunks of a task at one time, and to switch between the chunks regularly. Learners will then examine the concurrent.futures module, which contains objects to run threads and processes in an asynchronous manner, and to monitor their progress while they are still executing. Continue by learning how to use ThreadPoolExecutor, available in the concurrent.futures module. Finally, you examine the asyncio module in Python, which provides lightweight mechanisms for asynchronous executions of tasks.
9 videos |
1h 1m
Assessment
Badge
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COURSES INCLUDED
New Developments in Python
Python is an easy to learn, easy to read programming language widely used in scripting and application development. It's flexible and interpretive nature provides immediate feedback to users, making it one of the most popular programming languages today. Explore the roots of the Python language and discover its significant features. Examine the differences between versions 2 and 3 of Python and the process of migrating to the newer version. Delve into the new features that have been packed into subsequent releases of Python 3 and see how these can be adopted to build better applications. Finally, learn some of the best practices when it comes to building applications with Python - from the right syntax to improve readability to making your code easy to extend.
7 videos |
46m
Assessment
Badge
Getting Started with Python: Introduction
This 15-video course lets learners explore the basics of how to use the Python programming language. You will learn to set up with an interactive environment that allows you to develop and run Python scripts on your machine. Begin by installing Anaconda, an open-source distribution of the Python and R programming languages. You will learn to write your first meaningful program in Python, then create a Jupyter notebook, the most popular tool for writing and running Python code. You will learn how to do simple coding by using Python's Jupyter notebooks, and explore different Jupyter functionalities, including built-in functions. Learners will explore how to use a Python variable to store values, and learn to differentiate between variables of different types, and the different ways to assign values to variables. You will examine how variables act as containers, and you will learn how to change values that are inside a container. Finally, you will learn to use integers, floating-point numbers, strings, and to work with Boolean values.
15 videos |
1h 30m
Assessment
Badge
Complex Data Types in Python: Working with Lists & Tuples in Python
Learn how to work with lists, tuples, and strings in Jupyter notebook in Python in this 14-video course. You will discover similarities and differences between tuples and lists and see how strings are essentially just a list of characters. Begin with an introduction to lists, and then create and initialize lists in Python. You will then access and update list elements; add, remove, sort, and reverse elements from a list; execute built-in functions with lists, and create new lists from existing lists by using slicing operations. Next, examine how to extract specific elements from the original list using step size; perform list functions on strings; invoke functions on the string object; and access substrings with slicing operations. Receive an introduction to tuples, exploring the similarities between lists and tuples, then move on to understanding tuple immutability by specifying differences between lists and tuples. Then an introduction to other complex data types and using dictionaries and sets in Python. The concluding exercise concerns recalling differences and similarities between lists and tuples.
14 videos |
1h 39m
Assessment
Badge
Complex Data Types in Python: Working with Dictionaries & Sets in Python
This 9-video course helps learners explore dictionary data type in Python. Dictionaries are associative containers used to store key-value pairs. Given a key, finding the associated value is optimized by Python to be extremely efficient. First, receive an introduction to dictionaries in Jupyter Notebook in Python. You will learn how to create and initialize dictionaries, then learn about nesting complex data types within dictionaries. Continuing with the study of Python dictionaries, you will explore what functions and methods can be invoked on these dictionaries, such as modifying and updating dictionaries using dictionary methods. Next, you will be introduced to sets, another commonly used complex data type that Python supports. You will then create and initialize sets. This leads on to performing set operations such as union, intersection difference, and other set operations. You will also examine nested lists, and work with nested types within other complex data types. In the final tutorial, you will learn how to convert lists to dictionaries and vice versa. The concluding exercise entails recalling features of dictionaries and sets.
9 videos |
53m
Assessment
Badge
Complex Data Types in Python: Shallow & Deep Copies in Python
Explore copying operations on containers in Python in this 9-vdeo course, which examines the subtle distinction between shallow and deep copies. Changes made to shallow copies affect the original whereas with deep copies they do not. Learners begin by observing Jupyter notebook in Python, where you will be performing shallow and deep copies of Python strings. You will learn how to create shallow copies of lists, and then create deep copies of lists where changes to the copy do not affect the original. Following this, you will begin working with tuples, a process which you will discover is quite simple because tuples are immutable. So you will learn how to create shallow and deep copies of tuples. You will also learn how deep copies of dictionaries work, and perform shallow and deep copies of sets. In the closing exercise, learners are asked to recall how shallow and deep copies work for complex data types.
9 videos |
44m
Assessment
Badge
Conditional Statements & Loops: If-else Control Structures in Python
Learners will explore implementations of the order of precedence of operators, using if-elif-else statements to evaluate multiple conditions and conversions between various data types in Python, in this 15-video course. Key concepts covered here include how conditions in Python work, and how to evaluate conditions by involving primitive data types using if statements and complex data types using if statements. Next, evaluate multiple conditions for decision making with nested control structures; identify how to use the if-else statement to make decisions involving complex data types such as lists, tuples, and dictionaries; and learn how to convert an integer to a float and a float or an integer to a string, and vice-versa. Learners then observe how to convert primitive data types to complex data types, to convert between various complex data types, and to convert between various complex data types and view base conversions with Python built-in functions; and to solve various programming problems with Python built-in methods. Finally, you will learn to solve various programming problems by using if-elif-else statements and nested if-else statements.
15 videos |
1h 40m
Assessment
Badge
Conditional Statements & Loops: The Basics of for Loops in Python
Loops are one way to perform the same operations repeatedly in a program. For loops are the control structure to use when the repeated operations are performed on a sequence such as a list or a tuple. In this 9-video course, you will explore different ways to iterate over a sequence using for loops. Key concepts covered in this course include how to use for loops to process elements in a list and characters in a string; and how to code for loops to iterate over values in a tuple and the keys and values in a dictionary. Next, learn the function of associating an else block with a Python for loop; include if-else statements and other for loops within a for loop; how to generate a sequence of consecutive integers with the range function; and how to use the range function to iterate over a large range of values and apply it within nested for loops. Finally, observe how to write for loops in order to iterate over 1-dimensional and 2-dimensional sequences.
9 videos |
1h 1m
Assessment
Badge
Conditional Statements & Loops: Advanced Operations Using for Loops in Python
Explore how iterating over elements using for loops can be controlled using the break and continue statements in Python. Creating sequences from other sequences using comprehensions is also covered in this 9-video course. Key concepts covered here include how to terminate a for loop when a specific condition is met using the break statement; learning how the break statement affects the code in the else block of a for loop; and observing how to skip an iteration of a for loop when a specific condition is met using the continue statement. Next, learn how to use the continue statement along with the break statement within the same for loop; learn the fact that no action is performed under specific conditions by using the pass statement; and create a list out of the contents of another list using a comprehension. Finally, you will learn about conditions in list comprehensions in order to filter elements used in the source list and to define values in the newly created list.
9 videos |
1h 5m
Assessment
Badge
Conditional Statements & Loops: While Loops in Python
While loops are one way to keep repeating a set of actions until a specific condition is met in Python. In this 11-video course, learners explore the use of while loops, considerations when implementing while loops, and use cases for while loops and for loops. Key concepts covered here include implementing a basic while loop and recognizing what conditions cause it to become an infinite loop; learning to use while loops to carry out actions while evaluating expressions based on numerical and string data; and examining while loops whose iterations depend on user input data. Next, learn syntax for defining while loops within a single line; learn to iterate over a list of elements with while loops; and learn to iterate over multiple lists and tuples with while loops. Learn when it is appropriate to use break keyword to stop a while loop, and learn to break out of a while loop and recognize use of the pass keyword within such loops. Finally, learn skip steps in individual iterations of a while loop using the continue statement.
11 videos |
1h 19m
Assessment
Badge
Functions in Python: Introduction
Explore how Python facilitates code reuse by using functions in this 17-video course, which shows learners how to define functions, learn passing arguments to functions, and returning values from functions. The functions you will examine change the state of the program, may have side effects, and have observable effects other than their return values. Since functions with side effects are hard to parallelize and use in a distributed environment, you will learn correct ways of returning values from functions. First, you will learn how to invoke functions by using both positional and keyword arguments. You will next work with positional input arguments in custom functions, and learn that these are required arguments, and how to order these arguments to invoke your function. You will next learn to use variable length arguments in defining custom functions. Finally, you will learn how keyword arguments or named arguments are a way to make the intent behind function invocation absolutely explicit, and help prevent bugs in programs that are especially hard to detect.
17 videos |
2h 3m
Assessment
Badge
Functions in Python: Gaining a Deeper Understanding of Python Functions
This 13-video course offers learners an in-depth exploration of Python functions, by focusing on nuances such as argument passing by value and reference, and local and global variables. In this course, you will examine how functions are first-class citizens in Python, as with other data types. You will examine how Python allows functions to be stored in variables, passed into other functions as arguments, and returned from functions as return values. Next, you will learn how to identify and apply differences between parsing arguments by value and reference. Examine how Python treats functions on par with other data types, a key attribute of a program seeking to support the functional programming paradigm; and learn how to work with use and throw functions by using lam das. This course then covers how lightweight functions for one-off use called lambda functions or anonymous functions play an important role in keeping Python code both succinct and readable. Finally, you will learn how to appropriately choose between local and global variables for use in your program.
13 videos |
1h 25m
Assessment
Badge
Functions in Python: Working with Advanced Features of Python Functions
This course explores advanced Python function topics such as recursion, closures, and using generator functions to generate sequences. In 12 videos, you will learn how to use decorators to add functionality to code; examine how recursion can be used to construct code to solve complex problems; and learn to write a terminating condition for a recursive function. Next, you will learn how to use an Iterator to respond to a built-in next () function. Learners will also examine closures, and how as functions they maintain their own lexical environment; and explore how closures are functions that can yield dramatic results in the distributed processing of code, and are widely used in the implementation of distributed processing frameworks. Then you will learn how to use generator functions to generate sequences. You will learn how sequences can iterated upon by other parts of your program. Finally, you will learn that using decorators offers simple ways of invoking higher-order functions.
12 videos |
1h 26m
Assessment
Badge
Data Structures & Algorithms in Python: Fundamental Data Structures
Explore Python data structures and delve into the details of some of the basic structures, such as linked lists, stacks, and queues. Key concepts covered in this 12-video course include the metrics on which algorithms and operations on data are evaluated; learning how the performance of operations and algorithms is expressed in terms of size of input; and learning about linked lists and their contents and structure. Next, study different ways in which nodes can be added to a linked list and how search operations work on this data structure; learn methods to remove nodes from a linked list and the process of reversing the order of nodes in this data structure; and learn techniques used to keep track of numbers of elements in linked lists. You will examine workings of a stack data structure, including the addition and removal of elements; learn some of the operations on stacks, such as ISEMPTY and ISFULL, and the complexities of different stack operations; and learn the queue data structure and how to compare it to stacks.
12 videos |
1h 19m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Data Structures
Examine operations that have different values of time complexity and delve into implementation of basic data structures, such as linked lists, stacks, and queues in Python, in this 13-video course. Key concepts covered here include operations that run in constant time regardless of input; code whose time complexity varies directly with value of input; and tasks whose time complexity varies linearly with size of input. Next, you will learn about operations whose time complexity varies as the square of input size; how to use native queue class of Python and perform standard queue operations; and how to code a queue class for many standard queue operations, such as enqueue and dequeue. Then, learn how a Python list can be used as a stack by loading and unloading elements, and how to implement a custom stack class for common stack operations. Finally, study code functions to perform search and delete operations in linked lists and reverse the ordering of its nodes; and create a linked list and test out various operations that have been defined.
13 videos |
1h 29m
Assessment
Badge
Data Structures & Algorithms in Python: Sorting Algorithms
In this 11-video course, learners explore workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures. Key concepts covered here include various properties of sorting algorithms when selecting the right one for your data; the operations involved when sorting a list of values by using the selection sort algorithm; and the process of a bubble sort when applied to a list of values. Next, you will learn about the performance of the bubble sort on various measures such as time, space, and number of swaps; how to describe the steps involved in performing an insertion sort and compare it to the bubble sort; and learn the workings of the shell sort and the performance metrics of this divide and conquer algorithm. Finally, you will learn the process of sorting a list of elements using merge sort and list the complexity of this algorithm on various measures; and learn how the quicksort algorithm partitions and sorts a list of elements.
11 videos |
1h 14m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Sorting Algorithms
Examine the Python implementation of common sorting algorithms such as selection sort, bubble sort, and insertion sort, as well as divide and conquer sorts such as shell sort, merge sort, and quicksort, in this 10-video course. Key concepts covered in this course include how to write the code to implement a selection sort; how to implement the bubble sort algorithm in Python; and how to code a function to implement the insertion sort algorithm. Next, you will observe how to write the code to implement the divide-and-conquer shell sort algorithm; how to invoke the shell sort algorithm on an array of integers and examine the output at each iteration to understand how it works; and how to code a function to implement the merge sort algorithm and test it on an array of integers. Finally, learn how to write the partition and quicksort functions in order to implement a quicksort; and how to apply quicksort on an array of integers and analyze the results at each iteration to understand how the algorithm works.
10 videos |
1h 10m
Assessment
Badge
Data Structures & Algorithms in Python: Trees & Graphs
This 13-video course explores the theory of graph and tree data structures in Python. Learners will examine a specific type of tree: the binary search tree, its structures and properties. You will then observe how to execute common tasks in binary tree; examine the binary search algorithm; and review data structures of linked lists, stacks, and queues. Next, learners will examine how a binary tree structure offers several applications that cannot be done by using stacks or queues. The course demonstrates different depth first traversals, including pre-order, in-order traversals, and post-order traversals. Explore graphs, which are data structures used to model relationships, and different representations of a graph, and learn to model a vertex. Learners continue by observing how to represent an adjacency list as a graph, and examining the adjacency matrix, the adjacency list, and the adjacency set. Then you will explore graph traversal algorithms, including the topological sort. Finally, learn how to traverse through each of the vertices in a graph.
13 videos |
1h 32m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Trees & Graphs
Explore implementing trees and graphs in Python in this 14-video, hands-on course that contains only labs. In this course, learners will use Python 3 and Jupyter Notebooks as their IDE (integrated development environment). In the course labs, you will implement a binary search, define a binary search tree, and use code functions to work with those data structures. Next, you will implement algorithms to traverse trees, including how to perform a breadth-first traversal and depth-first traversal of the tree. Continue by examining graph data structure, and implementing different representations of graphs in Python by using an abstract class for a graph to represent graphs as both an adjacency set and an adjacency matrix. You will implement algorithms to traverse such graphs, including a breadth-first traversal and a depth-first traversal. This course then demonstrates how to run a test to check its implementation. Finally, learners observe how to implement a topological sort for a specific type of graph which is both directed as well as acyclic.
14 videos |
1h 25m
Assessment
Badge
Python Basics
Python is a very popular choice among professional developers for writing computer applications. In this course, you'll discover the basic features of Python, beginning with an overview of the Python language. Then you'll explore how to install Python and learn its basic syntax. You'll learn how to use variables with strings and how to save Python files, flow control, conditionals, comparisons, loops, and lists. You'll go on to how to use loops and lists, implement flow control in an application, and obtain user input. You'll discover functions in Python, Boolean and None data types, and custom functions. You'll learn about Python and JSON modules, file handlers, and how to use exception handling to solve problems. You'll discover the Python package manager (pip), Python Package Index, and the benefits of reusing libraries in Python programming. Finally, you'll discover HTTP requests, APIs, and dictionary data types in Python programming. This course was originally created by Global Knowledge (GK).
37 videos |
1h 7m
Assessment
Badge
Python Requests: HTTP Requests with Python
Learners can explore how to use the Python Request package which has simplified the task of constructing HTTP requests in this 16-video lab course, which explores different types of HTTP requests, and examines several ways to handle responses to those requests. Begin by learning how to use the Python request package to make a GET request for data from a server. Then you will observe how to construct a POST request to submit data to a host, and how to send it to a URL. Continue by learning how to use a HEAD request to check the resource information before downloading it by using GET, and how to examine request and response headers. Next, learners will examine a PUT request which has the same effect whether one makes the request once or multiple times, and which is used to overwrite an existing resource. You will learn to use DELETE requests. Finally, you will learn to address responses to requests in both JSON formatted or images.
16 videos |
1h 42m
Assessment
Badge
Socket Programming in Python: Introduction
Learners can explore basic concepts of Python socket programming, and how to communicate small amounts of data between Python applications by using either the same machine or over a network, in this 9-video course. Begin by learning how to use Python language to set up a communication line by creating a socket. Then learn to initialize a simple socket, and use it to transfer text data from one application to another. This course next demonstrates how to create a client app and server app in Python, and how each app uses a socket to communicate. Learners will observe a demonstration of how to transmit a Python dictionary and custom object over a socket connection. You will learn how to use a socket model to set up a simple TCP (transmission control protocol) socket to transfer text between applications. Next, learners will examine other properties of Python sockets, including its use with the context manager and the setting of a time-out for connections. Finally, you will learn to use the Pickle library to convey Python objects over a socket connection.
9 videos |
1h 2m
Assessment
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Socket Programming in Python: Advanced Topics
This 11-video course explores advanced features of Python sockets, including the transfer of large files over sockets, two-way communication, and differences between blocking and nonblocking sockets. You will learn to transfer large files over sockets by breaking them up into chunks, and to transfer images over TCP (transmission control protocol) sockets. Then you will learn how to transfer Python objects by using the pickle module. Next, learn how to create a chat application and use it to transfer several types of data from a server application to a client. Learners continue by exploring how to configure two-way communication over sockets by building a simple chat. This course examines the performance versus reliability trade-off when one uses blocking and nonblocking sockets. You will examine and compare TCP, a connection-oriented protocol, and UDP (Universal Datagram Protocol) which is connectionless. Finally, you will examine the performance versus reliability trade-off with a TCP and UDP, and why TCP is better suited for apps which require high reliability at the other end of the communication line.
11 videos |
1h 20m
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Security Programming: Python Scripting Essentials
Python is ubiquitous in modern desktop, server, and cloud computing environments. The ability to identify when to use Python, along with a working knowledge of how to write and run a Python script, are beneficial skills in secure coding. In this course, you'll explore the essential elements of Python scripting and the standard scenarios in which this language is preferable. First, you'll identify different Python scripts based on their features. Next, you'll learn how to work with variables, containers including lists, dictionaries, and tuples, conditionals, loops, and functions in a Python script. You'll learn how to carry out module imports and file reading and writing using a PowerShell script. Finally, you'll learn how to use a Python script to make a web request.
11 videos |
44m
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Building a CLI with argparse
It's common to need to deliver software that runs with a variety of options and a command line interface is a great way to let users invoke these various options. CLIs have been used to run programs since the early 1960s and are still relevant today. Their simplistic design, small footprint, and self-documentation make them ideal for automated or scheduled tasks. In this course, you'll review the history of CLIs and learn how to build a CLI using argparse, a module in the Python Standard Library. You'll examine positional and optional arguments, as well as how to use custom actions. Finally, you'll learn how to install a Python module as an editable package and explore the alternative, third-party packages for building a CLI - docopt and click. This course was originally created by Global Knowledge (GK).
9 videos |
39m
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Python Development: Getting Started with Programming in Python
Python is a beneficial language for use in a lot of development projects, particularly Java/C++ development. In this course, you'll learn the basics of Python programming. You'll start by installing Python on your local machine and practice writing code using the Python shell. Next, you'll perform basic math and logical operations in Python. You'll create Python variables and see how you can assign and access values stored in these variables. You'll then use built-in functions, which are part of the core Python programming language, to perform simple calculations and operations. Finally, you'll explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case. You'll then briefly examine the use of complex data types, such as lists, tuples, sets, and dictionaries. When you're finished with this course, you'll be able to execute simple Python commands on Jupiter notebooks.
13 videos |
1h 28m
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Python Development: Performing Operations with Complex Data Types
All values in Python are classified into data types. One of these, known as complex data types, facilitates using complex numbers. In this course, you'll learn how to work with complex data types in Python. You'll start by exploring the list data type, which contains an ordered collection of elements. You'll then perform several different operations on lists, such as accessing, adding, and removing elements and implementing slicing operations. Next, you'll work with tuples and examine how tuples contain an ordered collection of elements but are immutable in nature. You'll also work with sets and dictionaries. Finally, you'll explore the nuances of the copy operation for complex data types. When you're finished with this course, you'll be able to use the right Python data type to store your data and perform basic operations using these complex data types.
14 videos |
1h 54m
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Python Development: Working with If Statements, Loops, & Comprehensions
A handy procedure in Python for controlling the execution order of program statements is to implement branching operations using conditional statements, such as 'if' and 'else'. In this course, you'll learn how to use statements, loops, and comprehensions. First, you'll implement the conditional if statement. Then you'll use the else and elif statements. Moving on, you'll use Python's looping constructs, including the for-loop to iterate over elements in complex data types as well as over lists, tuples, and dictionaries. You'll use the while-loop and the break, continue, and pass keywords to further control loop execution. Finally, you'll implement list comprehension in Python, an elegant and efficient way of generating lists using 'for loops.' When you're finished with this course, you'll be able to write conditional statements in your code and perform looping and branching operations using for and while loops.
13 videos |
1h 45m
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Python Development: Defining, Configuring, & Invoking Functions
In Python, functions are essentially first-class citizens. They are objects in Python, just like other primitive and complex data types, and have a valuable purpose. In this course, you'll learn how to define and invoke functions in Python. First, you'll define a function using the def keyword and specify input arguments and return values from functions. You'll then work with positional arguments and keyword arguments. Next, you'll define functions with default values for arguments and a variable number of arguments. Along the way, you'll also examine how arguments can be pass-by-value or pass-by-reference. Finally, you'll explore the characteristics of Python functions that make them first-class citizens. When you're finished with this course, you'll have a solid grasp of the foundations of support for functions in Python and be able to use Python functions in your development work.
13 videos |
1h 44m
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Python Development: Leveraging Functions with Lambdas, Generators, Closures, & Decorators
Lambdas are great for on-off use and, once stored in a variable, behave exactly like other function objects in Python. In this course, you'll learn how to create anonymous functions in Python using lambdas. You'll start by creating generator functions in Python to generate infinite sequences using the yield keyword. You'll then illustrate how these generator functions can be resumed from just after the previous yielded value. Moving along, you'll demonstrate how closures in Python are nested functions that keep track of local variables in the outer function. You'll also illustrate how decorators - bits of code allowing you to modify other pre-existing code in your program - can be implemented using closures. When you're finished with this course, you'll have a good grip of functions in Python, which allow you to perform some incredibly complex and powerful operations.
11 videos |
1h 31m
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Python Development: Creating Classes, Handling Errors, & Importing Modules
Python classes act like blueprints for establishing a new type of object with its own set of properties and methods. In this course, you'll learn how to define and instantiate classes in Python. You'll start by using the init() method to initialize your class's member variables and the self keyword to reference a class's current instance. You'll then illustrate the differences between the self keyword in Python and the "this" keyword in Java. Next, you'll examine how errors in Python can be handled using the try-except-finally block and how the error handling mechanism in Python is similar to Java exception handling. Finally, you'll import other Python libraries into your current Python program, using classes and functions defined in one Python file in another file using the import statement. When you're finished with this course, you'll be able to set up Python classes for various uses in your development projects.
9 videos |
1h 16m
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Introduction to Using PyCharm IDE
PyCharm is one of the most intuitive and feature-rich integrated development environments (IDEs) available for Python development. Explore some of the important features of this IDE, such as debugging with breakpoints, Python package installation, and customizing syntax highlighting, in this 11-video course. Key concepts covered here include how to install and configure the PyCharm IDE on your system; how to customize syntax highlighting for various source files in Python project and how to minimize typing errors by using the auto-complete feature. Next, learn to apply name changes to variables and functions to all their references; learn the state of an application in the middle of code execution with the use of breakpoints; and use the step into feature to get inside function calls and step over to run them in one go. Finally, learn to pause code execution at a line only under a specified condition; and learn to use the resume button to ensure that code execution only pauses at breakpoints.
11 videos |
1h 16m
Assessment
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Flask in Python: An Introduction to Web Frameworks & Flask
Explore the steps involved in a web request and the role of web applications in this web development process in this 8-video course examining various pieces that can make up a web application, and the role of the web framework in defining it. Begin by observing a widely used framework, often defined as a microframework, written in the Python language, which is Flask. You will then explore the features of the Flask framework that are available either out of the box or via extensions. Following on from this, you will delve into the roles of routes in a Flask application and the options available when defining a route function. You will learn how to recognize the need for templates when defining a web site and describe the use of jinja for this purpose. The final tutorial in this course focuses on some of the commonly used extensions in the Flask applications and recalls the purposes they serve.
8 videos |
49m
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Flask in Python: Building a Simple Web Site Using Flask
You will begin this 12-video course by learning how to install Flask-a widely used web framework written in Python language-in a virtual environment on your development machine, and then write the code for a simple "Hello World" website by using Flask. You will explore how route definitions can be altered and the benefits of running your Flask app in debug mode. Next, define a route that renders an HTML page when a URL is accessed; download and use some boilerplate HTML files so your website definition need not begin from scratch, and modify the boilerplate cascading style sheet (CSS) and HTML definitions to customize the look of a website. Learn how to generate URLs dynamically by using the url_for function; create a base Jinja template that can be inherited by other templates, along with placeholders that can be overridden; and explore how to inherit the elements from a base Jinja template in a child template HTML file. Finally, learn how to define multiple routes to point to the same route function.
12 videos |
1h
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Building Web Apps Using Django: Introduction to Web Frameworks & Django
This 9-video course explores the concept of web frameworks and how they can speed up development of web applications, and examines the Django framework, a widely used framework written in the Python language. Learners begin by studying fundamentals of web requests, the steps and software required when processing web requests for static and dynamic websites. This leads into examining tasks involved in building a website and how web frameworks can speed up the process. Next, you will look at the Django framework and its features that can help to simplify web development, and the components of a Django application that are involved in processing web requests. Continue by observing what templates are in the context of Django and their use cases, and comparing Django models to database tables; then look at the role of the Django object-relational mapping layer (ORM) in mapping the two. Conclude the course by examining some of the built-in Django apps that developers can integrate into their own projects.
9 videos |
55m
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Building Web Apps Using Django: Building a Basic Website
Explore fundamentals of Django applications, from installation and the structure of a project, to implementations such as views, URLs, and templates, in this 12-video course. Begin by learning how to create a virtual Python environment and install Django, then how to generate a new Django project and describe various files that are created. You will discover how to start the built-in Django development server on the default port, as well as a specified port; define a view and URL pattern in Django to render the text "Hello World" in a web page; and generate a new app within a Django project. Learn about migrations in Django and using the manage.py script of a Django project to propagate model definitions to the database. Then observe working with Django URLs by configuring project and app-level URLs in Django; defining a view that renders an HTML file in its response; and downloading and using boilerplate HTML, CSS, and Javascript files in a Django project. Conclude by learning how to modify boilerplate HTML files to suit Django project requirements.
12 videos |
1h 18m
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Building Web Apps Using Django: Templates & User Administration
In this 11-video course, learners explore how to use templates to standardize components of a Django website, and different ways templates can be configured. Django is a widely used framework written in the Python language. Begin by learning how to add a new page to a Django website and use the Django template language to generate a URL for a URL pattern. Then move into creating a base template containing common elements for multiple pages in a Django website, and extending the base template and common elements defined within it while building individual pages in that Django website. Next, discover how to convey data from a view to a Django template in a dictionary, and apply styles defined in your CSS files to Django templates. Then move on to the Django admin interface, creating a superuser for your Django project and signing in to the Django user administration app, and using the Django admin interface to create new users. Finally, explore effects of assigning staff user status and specific permissions to Django app users.
11 videos |
1h 14m
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Building Web Apps Using Django: Models & User Registration
Django is a widely used web framework written in Python language. Explore the use of models to represent entities in a Django project, how they fit in with the project database, and how to implement user registration for a website by using various built-in Django tools in this 12-video course. Learners begin with Django models and defining entities in Django applications in model form, then learn how to propagate model definitions to a project's database by generating and running a migration script; create instances of a Django model and access model attributes; and view, update, and create instances of a Django model from the built-in admin interface. Next, explore user registration and create a view that uses Django's built-in user registration form; define the URL and template file for user registration pages for Django applications; convey notifications to website users with flash messages; and save data submitted in a user registration form by extending its definition. Conclude by learning how to install and use the Django-crispy-forms library to format a Django application's user registration page.
12 videos |
1h 23m
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Building Web Apps Using Django: Implementing Login & Logout
In this 10-video course, learners explore uses of Django's built-in login and logout views, and how to configure them. Django is a widely-used web framework using the Python language. Discover how to define a user profile, including how to define the model, set the image direction, and display profile information. Begin by building a user login page in a website with built-in Django objects, and then configure where a user is redirected to on a Django website upon successful login. Learn how to define logout template to serve as logout pages for a Django website; present different views for users who are signed into your Django website as opposed to regular users; and configure views in a Django application to render only when the user is signed in. Explore user profiles and defining the model for the profile of a user of a Django application; setting the location in a Django project directory where media can be stored; and displaying a user's information, including associated images, in a profile page.
10 videos |
1h 11m
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Building Web Apps Using Django: Generic Views
Explore various Django class-based generic views, which help to simplify the tasks of viewing, creating, editing, and deleting instances of Django models, in this 14-video course. Django is a widely used web framework written in the Python language. You will begin with a two-part tutorial on updating forms in a Django app: part 1 on defining forms and a view function, and part 2 on configuring update forms. Then explore how to use the built-in generic views: ListView to list instances of a model in your Django project; DetailView; CreateView; UpdateView, and also DeleteView. Discover how to configure permissions for the DeleteView; generate an archive of your Django model instances using the ArchiveIndexView; and create an archive of Django model instances, categorized by year, using the YearArchiveView. A two-part tutorial on applying finishing touches concludes the course: part 1 on defining an "About Us" page for your Django application, and part 2 on setting a customized 404 error page for your Django website.
14 videos |
1h 44m
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Machine Learning & Data Analytics
Explore critical machine learning (ML) and deep learning concepts and the various categorizations of algorithms and their implementations using Python.
10 videos |
1h 3m
Assessment
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Supervised, Unsupervised & Deep Learning
Discover how to implement various supervised and unsupervised algorithms of machine learning using Python, with the primary focus of clustering and classification.
10 videos |
1h 30m
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Deep Learning & Neural Network Implementation
Discover how to implement neural network with data sampling and workflow models using scikit-learn, and explore the pre and post model approaches of implementing machine learning workflows.
10 videos |
1h 2m
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Implementing ML Algorithm Using scikit-learn
Discover how to implement data classification using various techniques, including Bayesian, and learn to apply various search implementations with Python and scikit-learn.
10 videos |
1h 13m
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Implementing Robotic Process Automation
Discover how to implement Robotic Process Automation (RPA) using Python, and explore various RPA frameworks with the practical implementation of UiPath.
10 videos |
1h 2m
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Data Processing
Working with databases, regular expressions, and XML data are common tasks for DevOps in Python. Explore how to perform these common tasks.
9 videos |
48m
Assessment
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Applications
Explore web programming and GUI programming in Python.
12 videos |
1h 2m
Assessment
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Python - Introduction to NumPy for Multi-dimensional Data
ThisSkillsoft Aspire course explores NumPy, a Python library used in data science and big data. NumPy provides a framework to express data in the form of arrays, and is the fundamental building block for several other Python libraries. For this course, you will need to know basics of programming in Python3, and should also have some familiarity in working with Jupyter notebooks. You will learn how to create NumPy arrays and perform basic mathematical operations on them. Next you will see how to modify, index, slice, and reshape the arrays; and examine the NumPy library's universal array functions that operate on an element-by-element basis. Conclude by learning how to iterate various options through NumPy arrays.
11 videos |
58m
Assessment
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Python - Advanced Operations with NumPy Arrays
NumPy is oneof the fundamental packages for scientific computing that allows data to be represented in dimensional arrays. This course covers the array operations you can undertake such as image manipulation, fancy indexing, and broadcasting. To take this Skillsoft Aspire course, you should be comfortable with how to create, index, and slice Numpy arrays, and apply aggregate and universal functions. Among the topics, you will learn about the several options available in NumPy to split arrays. You will learn how to use NumPy to work with digital images, which are multidimensional arrays. Next, you will observe how to manipulate a color image, perform slicing operations to view sections of the image, and use a SciPy package for image manipulation. You will learn how to use masks, an array of index values, to access multiple elements of an array simultaneously, referred to as Sansi indexing. Finally, this course covers broadcasting to perform operations between mismatched arrays.
13 videos |
1h 7m
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Python Unit Testing: An Introduction to Python's unittest Framework
This 8-video course explores the unit-test framework in Python. To take this course, you should have experience in Python programming and the use of the Linux shell. The unit-test framework (also known as PyUnit) is modeled on JUnit and simplifies the automation of tests for Python applications. You will learn to use the unit-test framework to define tests for your application source code to ensure that it behaves in a specified manner. In this course, learners will write a sample test, and then expand the test scripts to include multiple tests. You will learn how to sequence the execution of tests in scripts, and how to filter out tests which do not require a specific run. Next, you will learn how to pass the output of test executions to identify the results of your tests, and how to diagnose test failures. You will learn how to run specific tests from among multiple tests in your scripts. Finally, this course demonstrates how to skip the execution of tests by using the skip decorator.
8 videos |
50m
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Python Unit Testing: Advanced Python Testing Using the unittest Framework
This 10-video course explores advanced features of Python testing uses of the unit-test Framework, and will examine several ways to optimize tests. A labs-only course using Linux Shell, it explores the unit-test framework, the pytest, and the doctest, and how to use them to automate the testing of all the functions in Python applications. You will learn how to bundle common operations for multiple tests into a special function or fixture, which make test scripts easier to view and maintain. Next, you will learn to adjust the scope of fixture functions to execute before each individual test, or to execute just once for the entire test case. Learners will examine how to create and execute a collection of test cases called test suites. You will explore the PyCharm IDE (integrated development environment), which includes support for several different testing frameworks. Finally, you will explore how PyCharm IDE simplifies the creation of tests by generating boilerplate code for test scripts with just a few clicks.
10 videos |
1h
Assessment
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Python Unit Testing: Testing Python Code Using pytest
Explore several types of testing frameworks for Python applications, including the unittest framework, pytest, and doctest, in this 12-video course. First, you will learn how to define and run tests, and how to streamline tests by using fixtures. You will learn the important features of the pytest framework to create small test units, and to define and run individual tests. Next, you will learn to group tests into multiple scripts, and how to execute multiple test scripts within a single run. Learners will observe how to create a simple test, and learn to increase the complexity by defining test scripts to cover multiple tests for your application. You will explore the execution and skipping of specific tests in scripts, then learn to simplify tests by using parameterization. You will learn how to apply filters on different tests, and to execute tests with a certain string in the test name, and examine the use of markers in a test. Finally, you will learn how to use fixtures to run operations common to multiple tests.
12 videos |
1h 13m
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Python Unit Testing: Testing Python Code Using doctest
This 8-video course explores several Python applications for testing, including the unit-test framework, pytest, and doctest. To take this course, you should have prior experience with Python programming, and familiarity with running commands from a Linux shell. This course focuses on doctests, and examines how the doctest module allows the definition of simple python tests within the docstrings in your source code. You will examine what syntax is needed when manually running tests from a Python shell, and how to copy over shells. Next, you will learn to capture the output and use it in your source file, then how to create an executable document for your source. This course demonstrates packaging a readme file, and the tests for a Python module. Learners will examine the bundling of documentation and tests into a single executable file. You will learn how to Ellipsis directive to address unpredictable outputs. Finally, you will learn to instruct your doctests to ignore whitespace characters within the outputs of a test by using the normalized whitespace directive.
8 videos |
43m
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Advanced Python Topics: File Operations in Python
Python includes functions and modules that simplify working with files. In this 11-video course, explore operations for standard text files and handling of formatted data such as JSON and CSV by using Python modules designed for such data. Learners begin with a look at some of the file operations in Python. Use Python's open function to open a file for reading, and differentiate between the read(), readline(), and readlines() functions. View differences between opening a file in write mode and append mode in Python. This leads on to distinguishing between the r+ and a+ modes to read from and write to a file; using load and loads functions of the json module to parse JSON data, and converting Python dictionaries and lists into JSON strings and files. Next, learn how to identify file formats that can be handled by the CSV module in Python, and convert Python dictionaries and lists into CSV files. The final tutorial concerns defining a customized file format, creating a CSV dialect, and using that to parse and write data.
11 videos |
1h 11m
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Advanced Python Topics: Exceptions & Command Line Arguments
In this 11-video course, learners can examine different types of exceptions that can be raised in Python and how they can be handled with except blocks. Explore execution of Python scripts from the command line, including use and parsing of command-line arguments. To begin, use a try and except block to handle a Python exception, then learn how to handle exceptions that your code may raise. Explore how exceptions are defined in a hierarchy and how related exceptions are caught and handled. Next, define multiple except blocks to handle various exceptions that can be raised by code; convert code prototyped in a Jupyter notebook into a Python script that can be executed from a shell, and run code from the Python shell and execute single-line and multi-line commands. Learn about parsing command line arguments, and use the sys and argparse module to access command-line arguments to a Python script, then parse and use the arguments passed to a Python script from the command line. Finally, learn to define command-line arguments by using argparse.
11 videos |
1h 12m
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Advanced Python Topics: Modules & Virtual Environments
Learners can explore built-in Python modules that allow you to perform many common operations without having to write the associated code, in this 9-video course. These operations range from random number generation to frequently used math calculations. You will learn how to recognize the features available in popular Python libraries such as NumPy, random, and datetime. Also, you will take a look at the steps involved in packaging Python code into a tar archive for distribution to end users; use pip to install a module in your environment and import it into your Python applications, and learn how to install the virtualenv tool and use it to create a virtual environment for Python applications. In the final two tutorials in this course, you will discover how to activate and run Python scripts from within virtual environments, and then install different packages in different virtual environments and recognize how they are isolated from each other.
9 videos |
59m
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Advanced Python Topics: Migrating from Python 2 to Python 3
In this 7-video course, learners discover key differences between Python 2 and Python 3, as well as learn how to perform a Python 2 migration to Python 3. Several other topics are also covered. Begin by observing how to set up the Jupyter Notebook integrated developer environment (IDE) to run and develop Python 2 code by installing a kernel for it. The next two tutorials will examine the differences between Python 2 and Python 3-part 1 will recall the variations in syntax and output for various operations such as print, division, and round for Python 2 versus Python 3; and part 2 explores differences in the round function behavior and different ways to accept user input in Python versions 2 and 3. Next, use the 2to3 conversion tool to identify the lines in your Python 2 scripts that need to be altered for Python 3 compatibility, and finally, explore how to convert a Python 2 script to be Python 3 compatible by using the 2to3 conversion tool.
7 videos |
39m
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Excel with Python: Working with Excel Spreadsheets from Python
This 13-video course explores how Microsoft Excel spreadsheets can be created, opened, and modified programmatically from within Python. Learners will review the Microsoft Excel object model, the attributes of the worksheet cell object which can be leveraged to create and modify workbooks programmatically. First, you will review VBA (Visual Basic for Applications) technology, before exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then you will learn how to use openpyxl (open pixel library) to manipulate Excel's object model programmatically from within Python. Continue by learning how to write spreadsheets by using openpyxl, and examining how existing Excel workbooks can be opened, as well as how new spreadsheet files can be created, and written out to disk. Finally, you will learn how Python iterators and indexing can be used to access and manipulate individual cells, ranges consisting of many cells, as well as entire rows and columns.
13 videos |
1h 16m
Assessment
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Excel with Python: Performing Advanced Operations
Learners can explore complex operations in Microsoft Excel workbooks, including the use of conditional formatting, named ranges, and merged cells, in this 17-video course. Microsoft Excel is the best prototyping tool for data analysis, an interactive functional programming environment, and a forerunner of Python. Begin by exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then observe the formatting, alignment, and other aesthetics in Python. You will work with the Python library openpyxl; examine data analysis, the use of pivot tables, and the locking of cell references by using the $ operator; and learn how to perform complex data analysis operations using pivot tables, sorting and filtering, and formulae with both absolute and relative cell references to enable efficient copy paste. You will learn to control the workbook appearance using conditional formatting and styles. Finally, this course demonstrates how to leverage the Python Pandas library to read a spreadsheet, to group and analyze data.
17 videos |
1h 29m
Assessment
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Excel with Python: Constructing Data Visualizations
This course explores how to use Python's openpyxl library to build visualizations such as line, bar, and bubble charts in Excel. In its 11 videos, you will examine how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation, before learning how to create line and bar charts in Excel, and learning how to use Python to control several properties of those charts, including line weights and style, data for the reference axes, formatting, and the position of ticks on those axes. Learners will observe how to construct data visualizations in Excel using Python. This course then demonstrates common types of visualizations that are supported in Excel, and how to programmatically replicate those visualizations from within Python. Finally, learners will observe demonstrations of the use of bubble charts to display three dimensions on a two-dimensional chart as well as stock charts to represent the opening, high, low, and closing prices of stocks in a single data visualization for the financial markets.
11 videos |
1h
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Python Classes & Inheritance: Introduction
In this 7-video course, learners will explore the concept of logical units, such as classes, and how they are used to hold state and behavior. Examine the modeling of is-a relationships by using inheritance and the advantages of object-oriented programming. You will begin with an introduction to classes, which are an integral part of Python programming. In this first tutorial, learn how state and behavior can be encapsulated in a single unit. This leads learners to examine how classes can be used as blueprints to create objects, and then to compare objects and instances to classes. Following on from this, you will take a look at inheritance, and model is-a relationship using inheritance. In the final tutorial in this course, you will explore the advantages of using object-oriented programming. In the concluding exercise, you will be asked to describe classes, define how state and behavior of a class are represented, list characteristics of class objects or instances, describe class inheritance, and list advantages of object-oriented programing with classes.
7 videos |
49m
Assessment
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Python Classes & Inheritance: Getting Started with Classes in Python
Explore implementations of Python classes, methods, and instance and class variables in this 15-video course. Learn how to implement private variables in Python classes and program problems with classes. Key concepts covered here include how to create classes by using Python; how to assign attributes to objects of classes; and how to initialize class variables by using the init special method. Next, you will observe how to initialize values for a class when you create objects; how to pass arguments to initialize the state of a class object; and additional methods in a class, as well as how class variables work. Learners will examine how class variables are different from instance variables and how class variables share memory across objects of a class; and work with variables that have their own memory in each object. Then examine getters and setters for each instance variable; learn to prevent inadvertent modification of instance variables; and learn to create a class to represent a real-world entity. Finally, observe how to parse information to create classes with a dictionary.
15 videos |
1h 33m
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Python Classes & Inheritance: Working with Inheritance in Python
In this 12-video course, learners will discover how to implement inheritance by using Python classes and explore coding examples of concepts such as base classes, derived classes, overriding methods, and polymorphism. Key concepts covered in this course include the default base class for all Python classes; how to model an is-a relationship by using inheritance; and how to invoke base class methods from subclasses. Next, you will observe how to define implementations for base class methods; learn to work with superclass and subclass hierarchies; and learn to define methods in a subclass and the idea of subclasses having additional attributes. Continue by learning about multiple inheritance levels in classes; multiple base classes for a single subclass; and polymorphism, an important characteristic of objects in object-oriented programming. Then you will learn to implement polymorphism in Python; learn about class inheritance and polymorphism; and learn to implement base and derived classes. Finally, learn to specify an init method to initialize member variables; learn about getters and setters for member variables; and learn to override a method.
12 videos |
1h 9m
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Python Classes & Inheritance: Advanced Functionality Using Python Classes
Examine the advanced features that you can implement by using classes in Python, such as special methods, iterators, class properties, and abstract base classes. Key concepts covered in this 14-video course include how to represent objects by using customized strings; performing addition operations on custom objects; and performing subtraction operations on custom objects. Next, observe how to perform multiplication operations on custom objects and perform floor division, modulo, and power-of operations. Then study learn built-in functions to work with custom data types; learn to execute for-loops on custom data types; and learn about properties on classes for intuitive use. Learn about properties using a simpler syntax; work with class methods to access and update class state; work with utility methods on classes; and learn how to use the abstract method to make classes that are not instantiable base classes. Finally, learners will be shown special methods and what they represent; learn to define a class and create a property within it; and observe how to differentiate between class methods and static methods.
14 videos |
1h 28m
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Automation Testing for Python
This course explores the prominent frameworks for testing Python-based applications, how to implement tests using Pytest and PyCharm, and also Pytest test parameterization. Begin this 14-video course with a look at the concept of automated testing and classifying the different types of automation testing. Then view the prominent Python testing frameworks, and features of DocTest, Nose, and UnitTest that can be used to automate testing of Python-based applications. Discover how to implement unit testing in Pytest by using the PyCharm integrated development environment (IDE), and the procedure to parameterize tests by using Pytest. Learn about configuring Robot and executing Python tests using the Robot framework; build and test application programming interfaces (API) using Flask, and explore the process of testing APIs built in Flask using Postman. Also learn how to configure the Behave framework for Python testing by writing feature files. To conclude the course, learners observe how to automate testing of web components by using Selenium with Python.
14 videos |
48m
Assessment
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Python AI Development: Introduction
Python is one of the most popular programming languages and programming AI in this language has many advantages. In this course, you'll learn about the differences between Python and other programming languages used for AI, Python's role in the industry, and cases where using Python can be beneficial. You'll also examine multiple Python tools, libraries, and use environments and recognize the direction in which this language is developing.
16 videos |
46m
Assessment
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AWS Lambdas in Python: Serverless Compute in Python with AWS Lambda
AWS Lambda is a serverless, event-driven compute service, meaning that it allows you to execute code when a specific event occurs, and abstracts the burden of maintaining infrastructure from you, the developer. Lambda functions are extremely powerful, but generally best-suited for lightweight interactive applications. Explore serverless computing and the benefits of AWS Lambdas. Discover the AWS Lambda dashboard and deploy a lambda function using Python runtime. Practice using blueprints and investigate the role of AWS Identity and Access Management in the successful outcome of a lambda function. Finally, configure a new REST API trigger through the API gateway service and expose that REST API using the curl utility. When this course is completed, you will recognize the roles and policies required for a lambda to run, and be able to create, deploy, and test lambda functions.
18 videos |
1h 54m
Assessment
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AWS Lambdas in Python: Using AWS Lambda with Containers, SES, SNS, & DynamoDB
A major benefit of using AWS Lambda is that you can easily integrate with other powerful AWS services like the Elastic Container Registry (ECR), AWS Simple Email Service (SES), DynamoDB, or Simple Notification Service (SNS). Learn how to deploy a lambda function based off a Docker container image and upload it to AWS via the ECR. Explore adding functionality to your lambda so that it can connect to Twitter. Modify your lambda to write out tweets to an S3 bucket and send automated emails. Finally, create a lambda function that triggers on a notification from an SNS and write out the contents of that notification to a DynamoDB table. Upon completion of this course, you will be able to easily deploy lambda functions as container images and seamlessly integrate AWS Lambda with ECR, SES, DynamoDB, and SNS.
17 videos |
2h
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Python Design Patterns: Principles of Good Design
Explore how the SOLID principles can help to make software designs easier to understand and maintain for Python developers. In this 14-video course, learners will examine the five SOLID principles-Single Responsibility, Open/Closed, Liskov's Substitution, Interface Segregation, and Dependency Inversion-as well as creational, structural, and behavioral design patterns. Key concepts covered here include the basic principles of good design in code; learning the Single Responsibility and Open/Closed principles of good design; and learning the Liskov's Substitution, Interface Segregation, and Dependency Inversion principles of good design. Next, learners will examine the principle of Least Knowledge and the Hollywood principle of good design; examine issues that may arise when classes do not implement the principle of Single Responsibility; and observe how to implement the principles of Single Responsibility and Open/Closed. Continue by learning how to design and implement the Liskov's Substitution principle, the Interface Segregation principle, and the Dependency Inversion principle. Finally, learners will study the three broad categories of design patterns and when to use each of them.
14 videos |
1h 34m
Assessment
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Python Design Patterns: Working with Creational Design Patterns
In this 16-video course, learners will explore the details and implementation of five commonly used creational design patterns: Singleton, Factory, Abstract Factory, Builder, and Object Pool. Key concepts covered here include how the Singleton pattern works and when to use it; how to write code for a simple implementation of the Singleton pattern; and how to implement the Singleton pattern by using a more Pythonic style and global objects in Python. Next, learn how the Factory and Abstract Factory patterns work; how to iteratively improve the design of code using refactoring; and how to design and implement the serializer with the Factory pattern. Continue by learning how to apply the Abstract Factory pattern to create a family of objects; how the Builder pattern works and how to implement a simple design for the Builder pattern; and how the Object Pool pattern works and how to implement the Object Pool pattern to limit the number of instances. Finally, learn how to improve the Object Pool pattern by making the object pool a singleton.
16 videos |
1h 48m
Assessment
Badge
Python Design Patterns: Working with Structural Design Patterns
Explore the design and implementation of five commonly used structural Python design patterns: Adapter, Decorator, Facade, Proxy, and Flyweight. In this 14-video course, learners examine how these patterns can be used for tasks such as working with legacy components, dynamically adding responsibilities, offering a simple client interface, controlling object access, and efficiently using lightweight resources. Key concepts covered here include design of the Adapter pattern and need for the pattern when working with legacy components; learning how to write code for the Adapter pattern to offer a consistent interface to clients; and learning design of the Decorator pattern and the importance for adding responsibilities dynamically. Continue by observing how to implement the Decorator pattern to allow adding responsibilities at runtime. Next, you will learn about the design of the Façade pattern and implementing the pattern to offer a simple interface to clients; learn to design and implement the Proxy pattern to control access to an object; and learn the design of the Flyweight pattern and how to implement the pattern to efficiently use lightweight resources.
14 videos |
1h 26m
Assessment
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Python Design Patterns: Working with Behavioral Design Patterns
Explore the design and implementation of five commonly used behavioral design patterns: Strategy, Chain of Responsibility, Observer, Command, and Iterator. Examine how these patterns can be used in Python built-in functions, in simple and complex use cases, for performing undo operations, and with Python special methods. Key concepts covered in this course include the Strategy pattern, how to design and implement the pattern, and how it is used in Python built-in functions; and learning the Chain of Responsibility pattern and how to write code to implement the pattern. Next, you will learn about the Observer pattern and how to implement the pattern for a simple use case and how to implement the pattern for a more complex use case. Finally, learners will study the Command pattern and how to implement the pattern to perform undo operations; and learn the Iterator pattern and its applications and learn to design an Iterator by using special methods in Python.
13 videos |
1h 26m
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Web Applications with Django: Introducing the Django Web Framework
Django, an advanced Python web framework, allows quick development of secure and sustainable websites. In this course, you'll discover how Django web requests work, which will involve using HTTP protocols, formatting content as HTML pages, using web servers to process requests, and distinguishing between static and dynamic websites. Moving on, you'll identify the steps involved in creating websites, which include reusing HTML elements over multiple pages on a website, customizing user experience by maintaining sessions, and querying databases for content. Next, you'll explore the features provided by web frameworks, particularly Django, that support and greatly simplify all these operations. You'll also investigate the use of Django templates. Finally, you'll become familiar with the migration process within Django and the use of the Django Model class to create subclasses that map to tables in a relational database.
9 videos |
57m
Assessment
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Web Applications with Django: Using Built-in and Custom Applications
The Django web framework simplifies creating websites and REST APIs through a wide variety of built-in features. In this course, you'll learn how to use some of these built-in features to create websites and apps. You'll start by installing the Django web framework inside a virtual environment. You'll then explore Django's out-of-the-box features, including the project structure, the shell, and the built-in admin app. Next, you'll build a Hello World website using a custom Django app. This process includes defining a URL that maps to a view, which then returns an HTTP response that can be viewed from a browser. Moving on, you'll explore the use of Django templates, which includes the use of base and derived templates. Finally, you'll work with the built-in admin app, examining how to administer users and groups and assign permissions.
14 videos |
1h 42m
Assessment
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Web Applications with Django: Working with Models
Creating websites and REST APIs is simplified through Django's built-in features. In this course, you'll learn how to use some of these features to build highly-performant websites and apps. You'll begin by examining how Django models are defined, migrated to a linked database, and registered with the built-in admin app. You'll then move on to using the Django ModelForm base class, which allows you to create a web page to create instances of your Django model. You'll then explore how to create a sign-in page for your Django website users and present signed-in users with a different view of the site. Finally, you'll cover how users can be allowed to sign out of your website.
10 videos |
1h 9m
Assessment
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Web Applications with Django: Models and Class-based Views
The robust websites and apps produced using Django suggest a much more complicated framework than is used. In this course, you'll build on your existing Django knowledge to perform some Django template language operations. You'll start this course by performing various query operations on your Django model instances from the Python shell. You'll also use the Django admin website to work with your models. You'll implement class-based views in Django, first using the ListView class to view multiple instances of a model before using the DetailView class to view individual records. Moving along, you'll use CreateView and UpdateView to generate and modify instances and implement a DeleteView for their easy removal. You'll round off this course by briefly exploring how to improve the aesthetics of your class-based views by incorporating HTML elements, such as tables, in their corresponding templates.
10 videos |
1h 22m
Assessment
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Web Applications with Django: Building Multiple Apps in a Project
A Django project is simply a web application consisting of one or more apps within it. Django's features ensure you can link multiple related project apps, create apps that accept and store user information, and trigger actions, such as sending emails. In this course, you'll practice carrying out these tasks in Django. You'll start by illustrating how images are incorporated within Django models, displayed on a web page, and stored on a file system while their paths are saved in the database. Next, you'll implement multiple separate but related apps within a Django project. Finally, you'll learn how to ensure a user's selection from a set of checkboxes is stored by your model and work with a user's email credentials to send them an email.
8 videos |
1h 3m
Assessment
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Web Applications with Django: Developing REST APIs
Among Django's many out-of-the-box tools is the REST Framework package, which includes libraries to build APIs. In this course, you'll install and work with this package to allow users to access and submit data to your web application. You'll start by defining a simple model whose instances can be accessed and manipulated using REST APIs. To make this happen, you'll use the built-in Django ModelSerializer class. You'll then wire up your Django REST API to return a list of JSON values from your Django model whenever a GET request is sent. You'll also use the Django REST framework's built-in web UI and the curl command-line utility to send POST requests to submit data to the server and use it to create model instances. Moving on, you'll briefly examine the use of HEAD and OPTION requests before wrapping up with a short exploration of PUT and DELETE requests.
10 videos |
1h 13m
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Flask in Python: User Interactions in Flask Applications
In this 12-video course, learners discover how to handle errors in Flask-a widely used web framework written in Python language-by serving a custom error page whenever a 404 error is invoked on a website. Learn how to configure a route in your Flask app so that POST requests can be submitted. Next, use the Flask debugger to record information in your application's log; convey the invocation of an operation to end users by using message flashing, and then highlight flashed messages by defining a style for them in a cascading style sheet (CSS) file. Next, explore how to install and use WTForms in Flask application to accept user input for registration, and define a login page by using field definitions and built-in form validations available in WTForms. Then include the two pages defined by using WTForms in the Flask application, and invoke the validators defined for WTForm elements to ensure that the user input is in the correct form. Finally, ensure that all built-in validators applied on the WTForm elements work as expected.
12 videos |
1h 20m
Assessment
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Flask in Python: User Authentication in a Flask Application
In this 14-video course, titled "User Authentication in Flask Applications," you will begin with an introduction to SQL Alchemy, then install it and use it to connect the Flask application-a widely used web framework written in Python language-to a SQLite database. You will observe how to use SQL Alchemy to generate relational database tables for each model defined in an application; execute queries against tables by using a SQL Alchemy model; and how to structure a Flask application for maintenance. Then you will modify import statements to account for restructuring of Flask app and test that functionality has not been affected. Use Bcrypt package to generate hashes of passwords so that they can be stored securely, and create a bespoke validator for fields in your WTForms. Next, learn how to enable users to log in and log out of a Flask application. You will access and display the three most recent reviews posted on your Flask website; learn how to test feedback display functionality; and display images in your Flask website.
14 videos |
1h 33m
Assessment
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Dash Python Framework: Dash for Interactive Web Apps
With Dash, you can create interactive web apps with elements such as buttons, dropdowns, sliders, range sliders, checkboxes, date pickers, and more. In this course, you'll learn how to get started with Dash, beginning with installing Dash and various extension libraries using the pip package installer. You'll move on to building web apps using Dash and the Plotly Express library. You'll also work with two other important Dash extension libraries - the Dash Core Components library and the Dash HTML Components library. You'll put all of these libraries together while exploring some of the default interactivity features, such as zooming and panning charts. You'll create a callback app where the title of a chart updates based on the values on a range slider before creating a more refined app with a callback that updates the chart itself and not just the title. Finally, you'll build a fully-fledged interactive scatter plot.
12 videos |
1h 32m
Assessment
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HTTP Requests with HTTPX: Introduction
Experience making and processing HTTP requests using HTTPX will help you integrate such requests into your web applications. In this entirely hands-on course, you'll dive into the mechanics of HTTP requests and responses using the HTTPX library. You'll begin by invoking basic GET requests to request data from a remote server. You'll then explore the different possible forms of responses - ranging from HTML content and structured JSON data to binary data, such as images and videos. Moving on, you'll learn to use POST requests to submit information to a remote server. Lastly, you'll cover a host of other HTTP requests that can be invoked with HTTPX, namely HEAD requests to retrieve headers, OPTIONS requests to get communication information, PUT requests to create or update resources, and DELETE requests to remove them.
12 videos |
1h 23m
Assessment
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HTTP Requests with HTTPX: Advanced Topics
Various HTTPX features are used to optimize the processing of HTTP requests. This course introduces you to some advanced techniques that use HTTPX to send and process HTTP requests. You'll start by looking at HTTPX streams, which allow the processing of large responses in chunks to reduce the load on memory resources. You'll then examine the HTTP response content that can determine how our application's subsequent actions are defined, including HTTP status codes, HTTP headers, and cookie usage. Next, you'll configure requests to handle redirects on the server side, set timeout values to prevent long waits due to network or server issues, and touch upon the compatibility of the Python Requests library with HTTPX. Finally, you'll focus on an essential feature of HTTPX - sending and asynchronously processing HTTP requests, which can significantly improve app performance.
15 videos |
1h 37m
Assessment
Badge
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Developing Apps with Tkinter: Getting Started
Desktop apps have been replaced by web applications in many cases, but remain widely used in many areas such as financial applications. Building desktop apps in Python is an important skill for many quantitative developers and financial data modelers. Python has many great libraries to create desktop applications including Tkinter, PyQt, and wxWidgets. You will focus on the Tkinter library which is a wrapper over the Tk library. Start this course by understanding some benefits and limitations of desktop applications. Explore some commonly-used libraries for GUI programming in Python, including PyQt, wxWidgets and PySimpleGUI, and contrast their strengths and weaknesses. After that, you will explore the Tkinter library. As you shall learn, this is a wrapper over the Tk library, which in turn is a wrapper of sorts over the tcl programming language. Tcl is a high-level programming language used to create Desktop GUIs. Explore the app you aim to build with Tkinter, demonstrating the use of database connectivity, interactive plotting widgets, as well as a complex GUI with many different widgets. Finally, install Tkinter and get up-and-running with deploying apps. To round out this course, you will create a simple app with a clock text label which automatically updates every second. After completing this course, you'll be able to identify the strengths and weaknesses of various Python UI libraries including Tkinter, PyQT, and wxWidgets and be ready to configure interactive widgets such as buttons and text entries.
12 videos |
1h 18m
Assessment
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Developing Apps with Tkinter: Configuring Interactive Widgets
Widgets such as buttons, labels, and user-entry fields for input form the core of any GUI. Tkinter includes button, entry, and label objects and geometry managers in Tkinter allow you to choose how to position your widgets. You will begin this course by creating an interactive button widget which displays an exit prompt when clicked. Discover how to instantiate text entry widgets where users enter text input to a box. Set up an app where the user enters obscured password credentials into a text entry widget and submits them using a button widget. Finally, explore the grid, pack, and place geometry managers in Tkinter. Upon completion of this course, you will be able to configure interactive widgets in Tkinter and choose between place, pack, and grid geometry managers to optimize app layout.
9 videos |
1h 1m
Assessment
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Developing Apps with Tkinter: Working with File Dialogs & Tree Views
File dialogs are powerful and versatile widgets that allow the user to navigate their local file system and upload a file, which can then be processed by the app. Tkinter offers file dialog functionality out-of-the-box and includes the tree view widget which can be used to represent either tabular or hierarchical data. Begin this course by creating Tkinter applications using an inheritance-based approach where you extend built-in Tkinter classes. Explore the tree view widget where you will represent simple tabular data in a tree view, create an app that displays the data in a Pandas data frame, and add scroll bars to a tree view. Finally, learn how to allow users to navigate and choose files using an upload file dialog, create a file picker, and add various dialogs and alerts related to the user's choice. Upon completion of this courses, you'll know how to allow an app to accept user uploaded files, validate and store files in a pandas data frame, and display the contents using a tree view.
11 videos |
1h 18m
Assessment
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Developing Apps with Tkinter: Menu Bars, Seaborn Visualization, & MySQL DBs
Buttons are useful widgets but they occupy screen real estate even when not being clicked and often clutter the UI of an app. Menus are a natural and popular choice to mitigate these weaknesses of buttons. Combining menus with visualization libraries such as Seaborn and databases such as MySQL can help you build a fully functional data analysis app in Python. Begin by adding menu bars to your app and link up actions to these menu bar items. Add a Seaborn line plot to your app which will allow the user to visualize the commodity price data they uploaded. You will then set up MySQL and run SQL code from the MySQL command line. Next, create a database that you will later connect to from an app, and load data from a file on your computer. Finally, you'll create an archive database to store old data and connect to MySQL from your app. After completing this course, you'll be able to add menus and menu items to a Tkinter app and leverage MySQL for database connectivity and Tkinter for visualizing data by integrating it with Seaborn.
12 videos |
1h 18m
Assessment
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Developing Apps with Tkinter: Tree View Operations & Login and Sign-up Pages
Displaying data using a tree view is useful, but even more useful are interactive tree views which perform actions in response to user inputs, such the selection of an item or a double-click on an item. Financial data is usually sensitive, so login and sign-up pages are great ways to authenticate a user of an app. Begin this course by adding an item-selection event handler to a tree view and create a similar stub handler for the double click. Discover how to modularize your code into different code files. After the modularization, confirm that the app is still functional. Then, you will add login and sign-up pages to the app. Finally, you will make an important change to the app by equipping it to figure out the schema of the relevant database table on the fly by referencing schema and metadata information. After completing this course, you will know how the tree view reacts to user actions, make the tree view robust to changes in the database schema, and add register and sign-in functionality to support authenticated data access.
10 videos |
1h 4m
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Web Apps with web2py: Getting Started
web2py is a powerful and popular Python web application development framework firmly built on the Model-View-Controller (MVC) paradigm, a popular design pattern often used for building user interfaces (UIs). A popular alternative to Django - another popular full-stack web framework - web2py offers an easy setup and a built-in integrated development environment (IDE). In this course, explore the fundamentals of web requests and responses, examine how web browsers and web servers interact, and identify the role of HTML and HTTP. Next, learn how web apps are created with frameworks and examine important Python web development frameworks such as Django, Flask, molten, and web2py. After that, compare web2py and Django and learn web2py's strengths and limitations. Finally, examine the web2py workflow, practice building your first simple web2py app, and explore the directory structure and support available for multiple languages and translation.
12 videos |
1h 27m
Assessment
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Web Apps with web2py: The Controller & View
web2py relies heavily on the Model-View-Controller (MVC) paradigm. The controller holds business logic in a web2py app, and the view file consists of HTML and has embedded Python code in the form of web2py template language. In this course, learn how to create your own web2py app. Start by working with the index view and About page, practice editing apps from your local machine using a familiar text editor, and compare the mapping between your machine's file structure and the web2py app directory structure. Next, examine the relationship between the controller and views, explore dictionaries and the view.html file, and identify important global variables such as response, request, db, and session. After that, explore session and request variables and how sessions are supported out of the box in web2py. Finally, learn how to deploy a simple app to a third-party web server such as PythonAnywhere.
11 videos |
1h 21m
Assessment
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Web Apps with web2py: Database Connectivity & the Model
Database connectivity is a crucial part of any full-stack web application and is the most convenient manner to persistently store data like user login credentials. web2py is built on the Model-View-Controller (MVC) paradigm with the model focused on connecting to databases and managing data in external sources. In this course, study the role of the model in web2py apps. Investigate the db.py file and learn how to integrate MySQL with web2py while using the MySQL database as a backend for your web apps. Next, explore how to install the MySQL server and MySQL Workbench tool, and practice integrating web2py with these technologies. Finally, work with the SQLFORM.grid widget, which is an extremely powerful and simple way to work with data from the model and incorporate it into your app.
9 videos |
1h 5m
Assessment
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Web Apps with web2py: Working with Prebuilt Bootstrap Templates
For full-stack web developers, frameworks like web2py help you construct all of the business logic and get the wiring and the app details right. When it comes to app appearance and aesthetics, it's wise to rely on powerful frameworks like Bootstrap. Bootstrap helps you build sophisticated user interfaces (UIs) using design templates that incorporate both CSS and JavaScript code for typography, forms, buttons, etc. In this course, explore prebuilt Bootstrap templates and examine how to modify one to fit your use case. Then, learn how to set up a real-world web app for an e-commerce store built atop the Bootstrap functionality. Finally, learn how to allow users to register and sign in to your app, and identify the differences in the views presented to the admin user, a signed-in user, and a user who isn't signed in.
8 videos |
52m
Assessment
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Web Apps with web2py: Decorators, Foreign Key Constraints, & Table Forms
When it comes to creating fully-fledged, professional-looking e-commerce web applications, there are a lot of little details that come into play. For instance, it's important to have functionality such as a shopping cart, or perhaps the ability for a user to browse the category of merchandise they may be interested in. In this course, learn how to add product creation functionality for the admin of the e-commerce site. Then, practice implementing a shopping cart using foreign key constraints. Next, identify how to use web2py decorators such as a login decorator to ensure that a user has to log in before they can view certain functionality. Finally, examine how to add in filtering functionality so your users can select the category of products to browse.
11 videos |
1h 23m
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Dash Python Framework: Leveraging Dash with User Input & Dash DataTable
If you've used Dash before, you'll know how quickly the native HTML table abstraction from dash_html_components can become complicated and cumbersome due to the need to create a TR tag for each row and then individual TD tags within each TR tag for each cell value. Using the dash DataTable abstraction mitigates all of these weaknesses. In this course, you'll practice this technique before using the Dash data table to display data in the form of tables in Dash apps. You may also know that you can harness the power of Dash using HTML components or components from the Dash Core Component library. In this course, you'll also get a chance to work with user input and buttons in Dash apps using the most appropriate components.
12 videos |
1h 41m
Assessment
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Dash Python Framework: Creating Widgets in Dash Apps
The Dash DAQ library can be used to represent data in ways that correspond to real-world physical measurement mechanisms, such as switches, thermometers, knobs, dials, gauges, LED displays, and tanks. In this course, you'll learn how to work with this library. In addition, you'll practice creating widgets using Dash core components. You'll also create Dropdowns, TextAreas, RadioButtons, and Checklists. Finally, you'll cover two important aspects of building web apps - building tabbed apps with different controls on each tab and accepting user upload of files. You'll build a web app that accepts a file for upload, either via drag-and-drop or via direct user navigation, and then checks whether the file is a .csv file and if so, displays the contents of that file in a DataTable.
14 videos |
1h 58m
Assessment
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EARN A DIGITAL BADGE WHEN YOU COMPLETE THESE COURSES
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.BOOKS INCLUDED
Book
Python BasicsOffering in-depth treatment of topics such as classes, inheritance, BST, and NumPy, this book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in industry.
5h 38m
By H. Bhasin
Book
The Quick Python Book, Third EditionWritten for programmers new to Python, this thorough book offers a clear, crisp updated introduction to the elegant Python programming language and its famously easy-to-read syntax.
8h 4m
By Naomi Ceder
Book
Clean Python: Elegant Coding in PythonDiscover the right way to code in Python. This book provides the tips and techniques you need to produce cleaner, error-free, and eloquent Python projects.
2h 42m
By Sunil Kapil
Book
Get Programming: Learn to Code with PythonFilled with practical examples and step-by-step lessons using the easy-on-the-brain Python language, this book introduces you to the world of writing computer programs without drowning you in confusing jargon or theory that make getting started harder than it should be.
6h 45m
By Ana Bell
Book
Beginning Python: From Novice to Professional, Third EditionCovering a wide array of Python-related programming topics, this insightful resource provides sound development principles and includes ten accompanying projects that will ensure you can get your hands dirty in no time.
9h 33m
By Magnus Lie Hetland
Book
Learn to Program with Python 3: A Step-by-Step Guide to Programming, Second EditionFully updated for Python 3, with code and examples throughout, this book explains Python coding with an accessible, step-by-step approach designed to bring you comfortably into the world of software development.
4h 46m
By Irv Kalb
Book
Beginning Programming with Python for Dummies, 2nd EditionIf you've never used Python or are new to programming in general, this hands-on resource is designed to help everyone, including nonprogrammers, get up and running with Python quickly.
5h 56m
By John Paul Mueller
Book
Python for Everyone, Second EditionFilled with programming examples, homework assignments, and lab exercises, this book provides an approachable introduction to fundamental programming techniques and design skills, and helps students master basic concepts to become competent coders.
13h 58m
By Cay Horstmann, Rance Necaise
Book
Python 3: Pocket PrimerProviding programmers with a sufficient knowledge of Python 3 to be able to work on their own projects, this book covers all of the basic concepts and features a chapter on PyGame, which allows a programmer to handle graphics, mouse and keyboard interaction, and play sounds and videos.
3h 14m
By James R. Parker
Book
Test Your Skills in Python LanguageGiving you an opportunity to check your proficiency in Python, this book provides more than 400 questions with detailed explanations that are represented by topic so that a Python programmer can go directly to testing a particular skill.
1h 24m
By Shivani Goel
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BOOKS INCLUDED
Book
Python BasicsOffering in-depth treatment of topics such as classes, inheritance, BST, and NumPy, this book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in industry.
5h 38m
By H. Bhasin
Book
Python Projects for Beginners: A Ten-Week Bootcamp Approach to Python ProgrammingImmerse yourself in learning Python and introductory data analytics with this book's project-based approach. Through the structure of a ten-week coding bootcamp course, you'll learn key concepts and gain hands-on experience through weekly projects.
4h 50m
By Connor P. Milliken
Book
Clean Python: Elegant Coding in PythonDiscover the right way to code in Python. This book provides the tips and techniques you need to produce cleaner, error-free, and eloquent Python projects.
2h 42m
By Sunil Kapil
Book
Get Programming: Learn to Code with PythonFilled with practical examples and step-by-step lessons using the easy-on-the-brain Python language, this book introduces you to the world of writing computer programs without drowning you in confusing jargon or theory that make getting started harder than it should be.
6h 45m
By Ana Bell
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Python for Data Science for Dummies, 2nd EditionWritten for people who are new to data analysis, this book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
7h 11m
By John Paul Mueller, Luca Massaron
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The Quick Python Book, Third EditionWritten for programmers new to Python, this thorough book offers a clear, crisp updated introduction to the elegant Python programming language and its famously easy-to-read syntax.
8h 4m
By Naomi Ceder
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Learn to Program with Python 3: A Step-by-Step Guide to Programming, Second EditionFully updated for Python 3, with code and examples throughout, this book explains Python coding with an accessible, step-by-step approach designed to bring you comfortably into the world of software development.
4h 46m
By Irv Kalb
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Python in Easy Steps, 2nd EditionInstructing you how to program in the powerful Python language, this book gives complete examples that illustrate each aspect with colorized source code.
2h 13m
By Mike McGrath
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Lean Python: Learn Just Enough Python to Build Useful ToolsProviding a unique "lean" approach to learning just enough Python to be efficiently productive, this practical resource explains only the essential aspects of Python without cluttering up your mind with features you may never use.
1h 9m
By Paul Gerrard
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Python GUI Programming with PAGE: Create Professional-Looking GUIs For Python Applications Efficiently and EffectivelyThis comprehensive book is your guide from installing the PAGE designer to mastering the creation of complex GUI interfaces.
3h 26m
By Gregory Walters
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Book
Foundations of Agile Python DevelopmentEmbracing concepts such as automation, effective code management, and test-driven development, this book introduces both the tools and techniques built and supported by the Python community.
6h 19m
By Jeff Younker
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Advanced Python Development: Using Powerful Language Features in Real-World ApplicationsIncluding a design and build of a real-world application example from prototype to production quality, this book builds on basic Python tutorials to explain various Python language features that aren't routinely covered.
8h 42m
By Matthew Wilkes
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Basics of Python Programming: Embrace the future of PythonOffering a variety of practical examples and conceptual problems along with their systematically worked out solutions, this book will come as a relief to the students wishing to go through a comprehensive work explaining the programming concepts of Python.
40m
By Pratiyush Guleria
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Python All-in-One For Dummies, 2nd EditionThis book covers everything from the basic elements of Python code to introductions to the specific applications where you'll use it. Intended as a hands-on reference, the focus is on practice over theory, providing you with examples to follow as well as code for you to copy and start modifying in the "real world"-helping you get up and running in your area of interest almost right away.
9h 5m
By Alan Simpson, John C. Shovic
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Let Us Python SolutionsProviding in-depth explanations of complex topics, this book follows a systematic approach for students, programmers, researchers, and software developers who wish to learn the basics of Python programming language.
1h 20m
By Aditya Kanetkar, Yashavant Kanetkar
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Python for Professionals: Hands-on Guide for Python ProfessionalsDesigned for programmers who have experience in at least one programming language, this book provides numerous tricks and tips that will make you a Python expert in no time.
5h 42m
By Matt Telles
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Clean Python: Elegant Coding in PythonDiscover the right way to code in Python. This book provides the tips and techniques you need to produce cleaner, error-free, and eloquent Python projects.
2h 42m
By Sunil Kapil
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Pro Python 3: Features and Tools for Professional Development, Third EditionIncluding insights and details about the Python philosophy, this book gives you the tools to write clean, innovative code while helping you refine your programming techniques and approaches to become a more productive and creative Python programmer.
6h 45m
By J. Burton Browning, Marty Alchin
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Beginning Django: Web Application Development and Deployment with PythonProviding all you need to get up and running with Django, this thorough book takes you from the basics of Django all the way through to cutting-edge topics such as creating RESTful applications.
12h 12m
By Daniel Rubio
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Practical Django 2 and Channels 2: Building Projects and Applications with Real-Time CapabilitiesTeaching you how to rapidly build your own e-commerce site by applying Django's battle-tested components, this book demonstrates Django's features and conventions to help you develop modern web applications quickly.
3h 12m
By Federico Marani
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Pro Django, Second EditionProviding in-depth information about advanced tools and techniques available in every Django installation, this book examines in great detail the complex problems that Python web application developers can face and how to solve them.
6h 44m
By Marty Alchin
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The Definitive Guide to Django: Web Development Done Right, Second EditionGuiding you through the creation of a web application reminiscent of chicagocrime.org, this book begins with the basics, such as installation and configuration, then moves on to more sophisticated features like RSS feeds, PDFs, and much more.
7h 41m
By Adrian Holovaty, Jacob Kaplan-Moss
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Practical Django Projects, Second EditionIntroducing the popular Django framework by way of a series of real-world projects, this book will show you how to work through the development of each project, implementing and running the applications while learning new features along the way.
4h 56m
By James Bennett
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Book
Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless CloudWorking through a series of common data science problems in an increasing order of complexity, this clear and practical book will help you take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection.
4h 11m
By Manuel Amunategui, Mehdi Roopaei
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Deep Learning with PythonBuilding your understanding through intuitive explanations and practical examples, this book introduces the field of deep learning using the Python language and the powerful Keras library.
5h 42m
By François Chollet
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Python Machine Learning Case Studies: Five Case Studies for the Data ScientistEquipped with practical examples along with code snippets, this step-by-step guide uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied.
2h 46m
By Danish Haroon
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Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using PythonConcise on theory, with a strong focus and a practical hands-on approach, this book will help you master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner.
4h 12m
By Manohar Swamynathan
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Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and RBridging the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better, this book will give you the confidence and skills needed when developing all the major machine learning models.
3h 16m
By V Kishore Ayyadevara
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Deep Learning with Python: A Hands-on IntroductionTeaching you the practical aspects of implementing deep-learning solutions using the rich Python ecosystem, this in-depth guide allows you to ramp up to such practical know-how in a short period of time so you can focus more on the domain, models, and algorithms.
1h 40m
By Nikhil Ketkar
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Python for Data Mining Quick Syntax ReferenceCovering each concept concisely with many illustrative examples, this book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.
1h 52m
By Valentina Porcu
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PyTorch Recipes: A Problem-Solution ApproachFor readers wanting to dive straight into programming PyTorch, this book adopts a problem-solution approach to PyTorch programming, includes deep learning algorithms with PyTorch and covers natural language processing and text processing.
1h 7m
By Pradeepta Mishra
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Book
Practical Django 2 and Channels 2: Building Projects and Applications with Real-Time CapabilitiesTeaching you how to rapidly build your own e-commerce site by applying Django's battle-tested components, this book demonstrates Django's features and conventions to help you develop modern web applications quickly.
3h 12m
By Federico Marani
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Beginning Django: Web Application Development and Deployment with PythonProviding all you need to get up and running with Django, this thorough book takes you from the basics of Django all the way through to cutting-edge topics such as creating RESTful applications.
12h 12m
By Daniel Rubio
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Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, Second EditionLeverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more.
10h 15m
By Robert Johansson
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Deep Learning with Python: A Hands-on IntroductionTeaching you the practical aspects of implementing deep-learning solutions using the rich Python ecosystem, this in-depth guide allows you to ramp up to such practical know-how in a short period of time so you can focus more on the domain, models, and algorithms.
1h 40m
By Nikhil Ketkar
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Pro Python 3: Features and Tools for Professional Development, Third EditionIncluding insights and details about the Python philosophy, this book gives you the tools to write clean, innovative code while helping you refine your programming techniques and approaches to become a more productive and creative Python programmer.
6h 45m
By J. Burton Browning, Marty Alchin
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Pro Python Best Practices: Debugging, Testing and MaintenanceTeaching you software engineering and coding best practices to write Python code right and error free, this book will show you how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding.
5h 2m
By Kristian Rother
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Professional PythonWith hands-on tutorials based on real-world scenarios, this useful guide goes beyond the basics to teach beginner- and intermediate-level Python programmers the little-known tools and constructs that build concise, maintainable code.
4h 40m
By Luke Sneeringer
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Python Crash Course: A Hands-on, Project-Based Introduction to ProgrammingIf you've been thinking seriously about digging into programming, this book is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.
8h 32m
By Eric Matthes
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Python for Everyone, Second EditionFilled with programming examples, homework assignments, and lab exercises, this book provides an approachable introduction to fundamental programming techniques and design skills, and helps students master basic concepts to become competent coders.
13h 58m
By Cay Horstmann, Rance Necaise
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Python 3: Pocket PrimerProviding programmers with a sufficient knowledge of Python 3 to be able to work on their own projects, this book covers all of the basic concepts and features a chapter on PyGame, which allows a programmer to handle graphics, mouse and keyboard interaction, and play sounds and videos.
3h 14m
By James R. Parker
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Python for Data Science for Dummies, 2nd EditionWritten for people who are new to data analysis, this book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
7h 11m
By John Paul Mueller, Luca Massaron
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Python Crash Course: A Hands-On, Project-Based Introduction to Programming, 2nd EditionA fast-paced, no-nonsense guide to programming in Python, this book teaches beginners the basics of with a focus on real projects.
8h 27m
By Eric Matthes
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Python Continuous Integration and Delivery: A Concise Guide with ExamplesBased on sample applications using numerous code examples, this book introduces Python programmers to the techniques and tools that enable a smooth and efficient software development process.
1h 59m
By Moritz Lenz
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Python BasicsOffering in-depth treatment of topics such as classes, inheritance, BST, and NumPy, this book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in industry.
5h 38m
By H. Bhasin
Book
Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI SystemsFeaturing a detailed business case on effective strategies on data visualization, this book looks at Python from a data science point of view and teaches proven techniques for data visualization as used in making critical business decisions.
2h 21m
By Ossama Embarak
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SKILL BENCHMARKS INCLUDED
Python Programming Mastery (Expert Level)
The Python Programming Mastery (Expert Level) benchmark evaluates your ability to recognize how code can be made more robust and maintainable by applying various design patterns. You will be evaluated on your skills in recognizing concurrency, creating and managing threads, using the asyncio library for asynchronous task executions, and using thread pools, process pools, and futures instances. A learner who scores high on this benchmark demonstrates that they have the skills to implement design patterns and concurrency in Python.
31m
| 31 questions
Python Programming Proficiency (Advanced Level)
The Python Programming Proficiency (Advanced Level) benchmark evaluates your ability to work with text and formatted files, handle exceptions in Python code, and handle script executions from the command line. You will be assessed on your skills in using built-in Python modules, packaging custom modules for distribution, implementing Python virtual environments, distinguishing between versions 2 and 3 of Python, and converting Python 2 scripts to be compatible with Python 3. A learner who scores high on this benchmark demonstrates that they have the skills to perform advanced Python operations like file and exception handling and can work with modules and packages.
23m
| 23 questions
SKILL BENCHMARKS INCLUDED
Programming Awareness (Entry Level)
The Programming Awareness benchmark will measure your ability to recognize key terms and concepts related to keys Software programming concepts. You will be evaluated on awareness of Python, Java, C, JavaScript, Angular, and software design principles. A learner who scores high on this benchmark demonstrates that they have the skills related to understanding key programming terminology and concepts.
24m
| 24 questions
Python Literacy (Beginner Level)
The Python literacy benchmark will measure your knowledge of getting started with Python. You will be evaluated on your ability to declare variables, use appropriate data types, use flow control statements, and perform operations with complex data types such as List, Tuples, Dictionaries, and Sets. You will also be assessed on your knowledge of how to use built-in functions and implement advanced features of Python functions. A learner who scores high on this benchmark demonstrates that they have the skills to write Python programs and develop applications using Python code.
37m 30s
| 25 questions
Python Web Literacy (Beginner Level)
The Python Web Literacy benchmark will measure your ability to build web applications using Flask in Python. You will be evaluated on your web development skills and ability to write effective code to implement unit testing, multithreading, concurrency in Python, and process HTTP requests in Python. A learner who scores high on this benchmark demonstrates that they have the ability to perform unit testing in Python and develop interactive web applications using Flask in Python.
30m
| 20 questions
Python Competency (Intermediate Level)
The Python Competency benchmark will measure your skills related to working with the PyCharm IDE and perform data wrangling in Excel. You will be evaluated on network programming skills in Python and implement complex operations in Excel workbooks using the Python openpyxl library. A learner who scores high on this benchmark demonstrates that they have the ability to perform advanced operations in Excel, construct data visualizations, write socket programs in Python, and have proven knowledge of various design patterns implemented in Python.
30m
| 20 questions
Python Mastery (Expert Level)
The Python Mastery benchmark will measure your familiarity with Python core features. You will be assessed on your ability to execute Python commands on Jupiter notebooks, perform operations using complex data types, use control flow statements, leverage functions with lambdas, generators, closures & decorators to perform some incredibly complex operations and handle exceptions. A learner who scores high on this benchmark demonstrates that they have the skills to develop Python programs and develop applications with Python code.
30m
| 20 questions
Python Programming Awareness (Entry Level)
The Python Programming Awareness (Entry Level) benchmark will measure your knowledge of the basic programming concepts of Python, such as variables, data types, and built-in functions. You will be assessed on your skills in using Jupyter Notebook to write and work with simple Python programs. A learner who scores high on this benchmark demonstrates that they have the skills to write and run a simple Python program using Jupyter Notebook.
10m
| 10 questions
Python Programming Literacy (Beginner Level)
The Python Programming Literacy (Beginner Level) benchmark will measure your ability to implement if...elif...else statements and while and for loops. You will be assessed on your skills in recognizing basic object-oriented programming (OOP) concepts, working with dictionaries and sets to store data in Python, and performing operations using lists, tuples, and strings in Python. A learner who scores high on this benchmark demonstrates that they have the skills to perform basic operations using control flow statements and complex data types in Python.
30m
| 30 questions
Python Programming Competency (Intermediate level)
The Python Programming Competency (Intermediate Level) benchmark measures your ability to identify situations where either deep or shallow copies are required. You will be assessed on your skills in implementing the powerful features of Python functions, recognizing functions as first class objects, using Python classes for advanced functionality, and working with recursion, closures, generators, decorators, and inheritance. A learner who scores high on this benchmark demonstrates that they have the skills to implement functional and object-oriented programming features in Python.
30m
| 30 questions
Python Data Structures Literacy (Beginner Level)
The Python Data Structures Literacy (Beginner Level) benchmark measures your knowledge of the purpose of data structures and the properties of linked lists, stacks, and queues. You will be assessed on your skills in implementing linked lists, stacks, and queues and the operations associated with those data structures in Python. A learner who scores high on this benchmark demonstrates that they have the skills to perform basic operations with data structures in Python.
17m
| 17 questions
Python Data Structures Competency (Intermediate Level)
The Python Data Structures Competency (Intermediate Level) benchmark measures your knowledge of the workings of commonly used sorting algorithms and how their implementations affect output performance. You will be assessed on your skills in implementing common sorting algorithms and divide and conquer sorts. A learner who scores high on this benchmark demonstrates that they have the skills to perform sorting algorithms in Python.
15m
| 15 questions
Python Data Structures Proficiency (Advanced Level)
The Python Data Structures Proficiency (Advanced Level) benchmark measures your knowledge of the properties of trees and graphs and the theory behind implementing these data structures in code. You will be evaluated on your skills in defining trees and graphs in Python 3 and coding traversal algorithms for these data structures. A learner who scores high on this benchmark demonstrates that they have the skills to work with graphs and trees in Python.
15m
| 15 questions
Python Socket Programming Competency (Intermediate Level)
The Python Socket Programming Competency (Intermediate Level) benchmark assesses your ability to use sockets in Python to transfer data between applications. You will be evaluated on your skills in recognizing and working with Python socket features that allow you to transfer large files and configure two-way communication. A learner who scores high on this benchmark demonstrates that they have the skills to recognize the basic concepts of Python socket programming and can implement the advanced features of Python sockets.
15m
| 15 questions
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Python for Developers Literacy (Beginner Level)
The Python for Developers Literacy (Beginner Level) benchmark evaluates your ability to install Python and work with variables, built-in functions, and simple Python data types. You will be assessed on your skills in creating and using lists and tuples, working with sets and dictionaries, correctly copying variables of complex data types, and distinguishing the similarities and differences across lists, sets, tuples, and dictionaries. A learner who scores high on this benchmark demonstrates that they have the skills to perform operations with simple and complex data types in Python.
16m
| 16 questions
Python for Developers Competency (Intermediate Level)
The Python for Developers Competency (Intermediate Level) benchmark evaluates your ability to build programs with control structures, iteratively loop over a block of code, and implement comprehension of lists, generators, and dictionaries. You will be assessed on your skills in creating and invoking Python functions, utilizing keywords and positional arguments, specifying default values for arguments, packing and unpacking varargs, and recognizing why functions are first class objects. A learner who scores high on this benchmark demonstrates that they have the skills to work with control flow statements and comprehensions, along with defining, configuring, and invoking functions in Python.
16m
| 16 questions
Python for Developers Proficiency (Advanced Level)
The Python for Developers Proficiency (Advanced Level) benchmark measures your ability to create and invoke lambda functions, implement closures and generator functions, and create and use decorator functions. You will be assessed on your skills in creating and instantiating Python classes, differentiating between Python and Java object-oriented programming, handling exceptions, importing modules, and using the __main__ variable. A learner who scores high on this benchmark demonstrates that they have the skills to leverage functions with lambdas, generators, closures, and decorators and can create classes, handle errors, and import modules.
15m
| 15 questions
SKILL BENCHMARKS INCLUDED
Python Unit Testing Literacy (Beginner Level)
The Python Unit Testing Literacy (Beginner Level) benchmark measures your ability to develop and debug Python applications using the PyCharm IDE. You will be assessed on your skills in defining and running tests for Python using the unittest unit testing framework. A learner who scores high on this benchmark demonstrates that they have the skills to work with the PyCharm IDE and use the unittest framework in Python.
15m
| 15 questions
SKILL BENCHMARKS INCLUDED
Python Web App Development with Flask Literacy (Beginner Level)
The Python Web App Development with Flask Literacy (Beginner Level) benchmark evaluates your ability to use the Python Requests package to make HTTP requests and parse the responses. You will be assessed on your skills in recognizing the need for a web framework and the features of Flask that speed up the development of a web application, as well as creating a basic website with Flask using boilerplate HTML files and templates. A learner who scores high on this benchmark demonstrates that they have the skills to make HTTP requests with Python and build a simple website using Flask.
20m
| 20 questions
SKILL BENCHMARKS INCLUDED
Web App Development with Django Literacy (Beginner Level)
The Web App Development with Django Literacy benchmark measures your ability to identify the purpose of web frameworks in web application development and recognize the related Django features. You will be evaluated on your knowledge of how to start the Django development server, render HTML files, use boilerplate materials, and perform migrations. A learner who scores high on this benchmark demonstrates that they have the skills to build a basic web site that renders HTML content with Django.
15m
| 15 questions
Web App Development with Django Competency (Intermediate Level)
The Web App Development with Django Competency benchmark assesses your knowledge of standardizing HTML elements and managing website users with the built-in Django admin app. You will be evaluated on your skills in representing entities in a Django project using models and implementing user registration and a login/logout feature in a web site. Additionally, you will also be measured on your ability to define pages for viewing, creating, and editing, and deleting Django model instances using the built-in generic view classes available in Django. A learner who scores high on this benchmark demonstrates that they have the skills to develop a full-fledged web application using Django.
30m
| 30 questions
SKILL BENCHMARKS INCLUDED
Python Unit Testing Literacy (Beginner Level)
The Python Unit Testing Literacy (Beginner Level) benchmark measures your ability to develop and debug Python applications using the PyCharm IDE. You will be assessed on your skills in defining and running tests for Python using the unittest unit testing framework. A learner who scores high on this benchmark demonstrates that they have the skills to work with the PyCharm IDE and use the unittest framework in Python.
15m
| 15 questions
Python Unit Testing Competency (Intermediate Level)
The Python Unit Testing Competency (Intermediate Level) benchmark measures your ability to recognize use cases for fixtures test suites and integrate your Python sources with their tests using the PyCharm IDE. You will be evaluated on your skills in using pytest and doctest to define and automate tests for your Python applications. A learner who scores high on this benchmark demonstrates that they have the skills to implement advanced Python testing using the unittest unit testing framework and test Python code using pytest and doctest.
18m
| 18 questions
SKILL BENCHMARKS INCLUDED
Excel Operations in Python Competency (Intermediate Level)
The Excel Operations in Python Competency (Intermediate Level) benchmark evaluates your ability to demonstrate the use of Python and the openpyxl library to create and modify Microsoft Excel spreadsheets. You will be assessed on your skills in performing complex data analysis operations using pivoting and formulae, controlling workbook appearance using conditional formatting and styles, building various types of visualizations using Python, and manipulating chart properties to customize their appearance. A learner who scores high on this benchmark demonstrates that they have the skills to manage Excel data, perform advanced operations, and construct data visualizations using Python.
25m
| 25 questions
SKILL BENCHMARKS INCLUDED
Python Django Literacy (Beginner Level)
The Python Django Literacy benchmark will measure your ability to develop secure and sustainable web sites using the Django framework. You will be evaluated on your ability to recognize the use of Django templates, the migration process within Django, and the use of the Django Model class. A learner who scores high on this benchmark demonstrates that they have the skills to use HTTP protocols, customize user experience by maintaining sessions, and query databases for content using the Django framework.
15m
| 10 questions
Python Web Development with Django Literacy (Beginner Level)
The Python Web Development with Django Literacy (Beginner Level) benchmark measures your knowledge of web requests, responses, and frameworks and how Django framework features help develop web apps. You will be evaluated on your ability to build a basic website using the Django framework and identify the different components involved in building a Django project. A learner who scores high on this benchmark demonstrates that they have the skills to develop simple web applications with Django.
15m
| 15 questions
Python Web Development with Django Competency (Intermediate Level)
The Python Web Development with Django Competency (Intermediate Level) benchmark measures your knowledge of implementing a simple Django model and deploying it to a linked database. You will be evaluated on your ability to use Django templates and the Django Model class, recognize the migration process within Django, and build web pages that allow interactions with Django model instances. You will also be evaluated on your ability to add and access an image in a Django model, create applications to accept and store information from users, and send emails from a Django app. A learner who scores high on this benchmark demonstrates that they have the skills to work with models and class-based views and can build multiple applications in a project.
18m
| 18 questions
SKILL BENCHMARKS INCLUDED
Python Web App Development with Flask Competency (Intermediate Level)
The Python Web App Development with Flask Competency (Intermediate Level) benchmark measures your ability to build an interactive website by accepting input using WTForms and conveying messages to the end users. You will be evaluated on your skills in implementing database integration and user authentication in a Flask application. A learner who scores high on this benchmark demonstrates that they have the skills to incorporate user interactions and implement user authentication in a Flask application.
15m
| 15 questions
SKILL BENCHMARKS INCLUDED
Python Dash Framework Competency (Intermediate Level)
The Python Dash Framework Competency (Intermediate Level) benchmark measures your ability to install Dash and its libraries, run a Dash app using the Python shell, create visualizations using the plotly.express API, and work with graph object instances and callback functions. You will be evaluated on your ability to use Dash to accept and validate user input and use date pickers. A learner who scores high on this benchmark demonstrates that they have the skills to develop interactive Python applications with the Dash framework.
12m
| 12 questions
Python Dash Framework Proficiency (Advanced Level)
The Python Dash Framework Proficiency (Advanced Level) benchmark measures your ability to perform data visualizations in Python using Dash frameworks. You will be evaluated on your ability to use submit buttons, HTML tables, DataTables, event handlers, and the Dash DAQ library to represent data. You will also be evaluated on your ability to create searchable and clearable dropdowns, use various components such as checklists, and configure interactive visualizations using parsed data. A learner who scores high on this benchmark demonstrates that they have the skills to develop interactive Python applications and create widgets in Dash apps.
13m
| 13 questions
SKILL BENCHMARKS INCLUDED
Python API Development Literacy (Beginner Level)
The Python API Development Literacy (Beginner Level) benchmark will measure your understanding of the mechanics of HTTP requests and responses using the HTTPX library. You will be evaluated on your ability to install the Flask-RESTful library, implement a simple API server to respond to requests, and develop handlers for GET and POST requests for a Python application using the molten framework. A learner who scores high on this benchmark demonstrates that they have the skills to handle requests and responses for APIs in Flask and molten frameworks.
22m
| 22 questions
Python API Development Competency (Intermediate Level)
The Python API Development Competency (Intermediate Level) benchmark assesses your ability to use HTTPX features to optimize the processing of HTTP requests. You will be evaluated on your ability to build REST APIs, use the Flask-RESTful request parser, customize the parser to validate input arguments, and bundle errors to display more user-friendly error responses. A learner who scores high on this benchmark demonstrates that they have the skills to use HTTPX to send and process HTTP requests, build REST APIs, and validate input requests in Flask.
21m
| 21 questions
SKILL BENCHMARKS INCLUDED
Python Desktop App Development with Tkinter Literacy (Beginner Level)
The Python Desktop App Development with Tkinter Literacy (Beginner Level) benchmark evaluates your knowledge of the strengths and weaknesses of various Python UI libraries and the basics of Tkinter UIs. You will be assessed on your readiness to configure interactive widgets such as buttons and text entries. Learners who score high on this benchmark demonstrate that they have the skills to recognize the basic features of Tkinter.
12m
| 12 questions
Python Desktop App Development with Tkinter Competency (Intermediate Level)
The Python Desktop App Development with Tkinter Competency (Intermediate Level) benchmark assesses your knowledge of configuring interactive widgets in Tkinter and choosing between place, pack, and grid geometry managers to optimize app layout. You will be evaluated on your skills in allowing an app to accept user-uploaded files, validating and storing files in a pandas data frame, and displaying the contents using a tree view. Learners who score high on this benchmark demonstrate that they have the skills to configure interactive widgets and work with file dialogs and tree views.
12m
| 12 questions
Python Desktop App Development with Tkinter Proficiency (Advanced Level)
The Python Desktop App Development with Tkinter Proficiency (Advanced Level) benchmark calibrates your knowledge of adding menus and menu items to a Tkinter app, leveraging MySQL for database connectivity, and integrating Seaborn with Tkinter for data visualization. You will be assessed on your skills in performing tree view operations and adding register and sign-in functionality to support authenticated data access. Learners who score high on this benchmark demonstrate that they have the skills to work with menu bars, Seaborn visualizations, and tree views in addition to connecting to MySQL DBs and implementing authentication in Tkinter.
15m
| 15 questions
SKILL BENCHMARKS INCLUDED
Python Web App Development with web2py Competency (Intermediate Level)
The Python Web App Development with web2py Competency (Intermediate Level) benchmark assesses your knowledge of creating and configuring web2py apps, wiring up controllers and views for web pages, using sessions and request variables, and deploying a web2py app to the PythonAnywhere server. You will be evaluated on your skills in using a model in web2py apps to connect with a database, integrating a MySQL database with a web2py app, and using the SQLFORM.grid widget to work with data from the model. Learners who score high on this benchmark demonstrate that they have the skills to work with controllers, views, and models.
12m
| 12 questions
Python Web App Development with web2py Proficiency (Advanced Level)
The Python Web App Development with web2py Proficiency (Advanced Level) benchmark calibrates your skills in modifying prebuilt Bootstrap templates, building an e-commerce application, adding functionality to register users, and presenting different views to admins and users in signed-in and signed-out modes. You will be evaluated on your ability to add administration functionality, implement foreign key constraints, and filter functionality to an e-commerce application. Learners who score high on this benchmark demonstrate that they have the skills to work with prebuilt Bootstrap templates, use decorators, and implement foreign key constraints and table forms in web2py.
12m
| 12 questions
