Prompt Engineering for Data: Leveraging Prompts When Working with Data

Prompt engineering, data science    |    Beginner
  • 12 videos | 1h 37m 32s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Python is a powerful programming language for data science, and pandas is a popular open-source data manipulation and analysis library in Python. Combined with prompt engineering techniques, working with data in Python is easy and intuitive, which allows you to be more productive and efficient. You will start this course by leveraging prompt engineering to work with pandas. You will explore libraries such as Matplotlib, seaborn, and Plotly, which are used for visualization and charting. With ChatGPT's help you will read data from a CSV file and inspect the DataFrame. You'll delve into pandas Series objects and explore their creation and manipulation. You will leverage prompt engineering techniques to access elements in a Series using index labels through loc, iloc, at, and iat functions and perform operations like modification and visualization. Finally, you will explore how to use pandas DataFrame objects and create basic DataFrames using lists and dictionaries for data assignment and inspection. You will also generate code to perform basic operations on DataFrames using tools such as ChatGPT and Bard.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Provide an overview of data analysis and visualization
    Outline the use of prompt engineering for code
    Import and set up pandas
    Explore the features of pandas series
    Work with indexes in pandas series
  • Index and filter series
    Perform filtering and aggregation
    Explore pandas dataframes
    View dataframe properties and features
    Perform dataframe indexing
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 15s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 10m 50s
    After completing this video, you will be able to provide an overview of data analysis and visualization. FREE ACCESS
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    3.  Introducing Prompt Engineering
    5m 50s
    Upon completion of this video, you will be able to outline the use of prompt engineering for code. FREE ACCESS
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    4.  Getting Set Up for Data Analysis and Visualization
    12m 55s
    Find out how to import and set up pandas. FREE ACCESS
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    5.  Creating pandas Series Objects
    13m 1s
    In this video, we will explore the features of pandas Series. FREE ACCESS
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    6.  Using ChatGPT to Understand Index Labels for pandas Series
    9m 20s
    In this video, you will learn how to work with indexes in pandas Series. FREE ACCESS
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    7.  Indexing and Filtering Series Using .loc[] and .iloc[]
    4m 26s
    During this video, discover how to index and filter Series. FREE ACCESS
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    8.  Performing Operations on pandas Series
    10m 11s
    Learn how to perform filtering and aggregation. FREE ACCESS
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    9.  Creating pandas DataFrame Objects
    9m 6s
    In this video, we will explore pandas DataFrames. FREE ACCESS
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    10.  Viewing DataFrame Properties with Generative AI's Help
    6m 25s
    In this video, find out how to view DataFrame properties and features. FREE ACCESS
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    11.  Performing DataFrame Indexing Using .loc[] and .iloc[]
    10m 28s
    Discover how to perform DataFrame indexing . FREE ACCESS
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    12.  Course Summary
    2m 44s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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