This advanced course explores approaches to building and implementing visualizations, after you have an understanding of your data. Learn plotting and graphing using Python libraries like Matplotlib, ggplot, bokeh, and Pygal, and discover how to build advanced charts using Python and Jupyter Notebook. The also course covers the visualization capabilities of R and ggplot2 and how to build charts and graphs with the software.

LEARNING OBJECTIVES

By the end of the course, you will be able to:

• Recognize the importance and relevance of data visualization from a business perspective
• Consider libraries that can be used in Python to implement data visualization
• Set up a data visualization environment using Python tools and libraries
• Examine the prominent data visualization libraries that can be used with Matplotlib
• Create a line chart with Pygal, create an HTML directive to render the line chart, and render the line chart
• Identify the different types of charts that can be implemented and their relevance in data visualization
• Create Matplotlib animations
• Analyze graphical capabilities of R from the perspective of data visualization
• Create heat maps using R, create scatter plots using R, and create area charts using R

WHO WILL BENEFIT

IT technicians and business analysts familiar with data visualization who are looking to advance their presentations and dashboards.

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