Visualizing Data & Communicating Results in Python

Instructor: Sharon Jason

Skills you'll gain

  •   Interactive Data Visualization
  •   Integrated Development Environments
  •   Computer Programming
  •   Jupyter
  •   Graphing
  •   Data Visualization Software
  •   Scatter Plots
  •   Box Plots
  •   Animations
  •   Scientific Visualization
  •   Plot (Graphics)
  •   Histogram
  •   Matplotlib
  •   Statistical Visualization
  • There are 3 modules in this course

    This course is designed for learners with limited coding experience, providing a foundation for presenting data using visualization tools in Jupyter Notebook. This course helps learners describe and make inferences from data, and better communicate and present data. The modules in this course will cover a wide range of visualizations, which allow you to illustrate and compare the composition of the dataset, determine its distribution, and visualize complex data, such as geographically based data. It is recommended that you complete Data Analysis in Python before taking this course. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.

    Visualization: Intermediate Matplotlib

    Visualization: Advanced Matplotlib

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