Free Online Data Visualization Course | Alison

Data Science - Visualizing Data and Exploring Models - Revised

Learn about data science techniques, applying visualizations to display data, feature engineering methods, and more!

Data Science
Free Course
This free online Data Visualization course teaches you about visualizing data and exploring models. Data visualization is a highly useful way to explore data and can help you determine relationships between columns. With this course, you will learn how to apply visualizations to display your data and about feature engineering and constructing machine learning models. You will learn how to evaluate your model in Azure ML, R, and Python, and more!
  • Duration

    1.5-3 Hours
  • Assessment

  • Certification

  • Responsive

  • Publisher

    Channel 9





View course modules


This course begins by discussing the importance of data exploration. It will teach you what to use for data visualizations in R and in Python. You will study different plots for different views such as scatter and line plots, bar plots, histograms, box plots, violin plots, Q-Q plots. You will also learn that scatter plot of individual columns can be useful for detailed exploration of the features in your dataset.

You will then study feature engineering which is the process of using domain knowledge of the data to create features that make machine learning algorithms work. You will look into models which are evaluated based on statistics about the errors, or residuals, in the predicted values. You will study the features and methods available in R and Python for creating Machine learning models including the process and options for evaluation.

Learn about about data science theory and practice with this free, online course. Upon completing the course, you will have a better understanding of the functions of exploratory data analysis and what factors can affect your views of data, as well as a much better insight into the different types of charts to help visualize your data as well as the libraries and packages available for R and Python. Start this course today to improve your data literacy! 

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Learning Outcomes

Upon successful completion of this course the learner will be able to:

  • Discuss the importance of data exploration
  • Recognize what you use for data visualizations in R
  • Recognize what you use for data visualizations in Python
  • Identify the different types of plots or charts you can use to visualize your data
  • Discuss the process of feature engineering
  • Identify features and methods available in R for creating Machine learning models
  • Identify features and methods available in Python for creating Machine learning models
  • Outline the process and options for evaluating your machine learning model


All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire an official Certificate, which is a great way to share your achievement with the world. Your Alison Certificate is:

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