AWS Certified Machine Learning: Data Analysis Fundamentals

Amazon Web Services    |    Intermediate
  • 12 videos | 34m 2s
  • Includes Assessment
  • Earns a Badge
Rating 4.1 of 24 users Rating 4.1 of 24 users (24)
Data Analysis is a primary method for deriving valuable insight from raw and unstructured data. The appropriate application of data analysis techniques is vital in deriving only the relevant insight and factual knowledge from available data. Picking the correct data distribution or visualization technique can become critical to the overall data analysis results. Using this course, become familiar with the core foundations of data - the essential ground for any data analysis and machine learning operation. Examine the various types of data that exist, inherent data distributions, both traditional and modern methods of visualizing data, and how time series analysis works. When you've completed this course, you'll be able to describe the core concepts of data analysis and implement some valuable visualization and analysis techniques using Python. This course will prepare you for the AWS Certified Machine Learning - Specialty certification exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Differentiate between categorical and numerical data types
    Define bernoulli, uniform, and binomial data distributions
    Define normal, poisson, and exponential data distributions
    Describe the key role of visualization in communicating information from analyzed data
    Name and describe traditional graphic types used in data analysis
  • Name and describe modern graphic types used in data analysis
    Work with python toolkits to implement various types of data visualization
    Describe what's meant by time series analysis and define its role in data science
    Recognize what's meant by advanced time series analysis concepts, such as trends, seasonality, and autocorrelation
    Work with time series data in python, implementing data analysis pipelines
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 3s
  • 2m 51s
    Learn how to differentiate between categorical and numerical data types. FREE ACCESS
  • Locked
    3.  Bernoulli, Uniform, and Binomial Data Distributions
    2m 38s
    In this video, you will learn how to define Bernoulli, uniform, and binomial data distributions. FREE ACCESS
  • Locked
    4.  Normal, Poisson, and Exponential Data Distributions
    3m 40s
    During this video, you will learn how to define normal, Poisson, and exponential data distributions. FREE ACCESS
  • Locked
    5.  The Primary Role of Data Visualization
    2m 17s
    In this video, discover how visualization can help communicate information from analyzed data. FREE ACCESS
  • Locked
    6.  Data Visualization - Traditional Graphic Types
    2m 12s
    Discover how to name and describe traditional types of graphics used in data analysis. FREE ACCESS
  • Locked
    7.  Data Visualization - Modern Graphic Types
    2m 14s
    In this video, you will name and describe modern graphic types used in data analysis. FREE ACCESS
  • Locked
    8.  Implementing Data Visualization with Python
    7m 33s
    After completing this video, you will be able to work with Python toolkits to implement various types of data visualization. FREE ACCESS
  • Locked
    9.  Time Series Analysis in Data Science
    2m 25s
    In this video, you will learn how to describe what is meant by time series analysis and its role in data science. FREE ACCESS
  • Locked
    10.  Advanced Time Series Analysis Concepts
    1m 52s
    Upon completion of this video, you will be able to recognize what is meant by advanced time series analysis concepts, such as trends, seasonality, and autocorrelation. FREE ACCESS
  • Locked
    11.  Implementing Time Series Analysis in Python
    4m 25s
    During this video, you will learn how to work with time series data in Python by implementing data analysis pipelines. FREE ACCESS
  • Locked
    12.  Course Summary
    53s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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