David Gold is a Ph.D. candidate in Environmental and Water Resources Systems (EWRS) with the Reed Research Group at Cornell University. His research focuses on water supply planning under conditions of deep uncertainty that stem from climate change and population growth. Professor Gold has a Bachelor of Science degree in Civil and Environmental Engineering from Lafayette College and a Master of Engineering degree in EWRS from Cornell. Prior to arriving at Cornell, he worked as a design engineer for the USDA Natural Resources Conservation Service in Rhode Island. When Professor Gold is not teaching or doing research at Cornell, he likes to play the banjo.
In this course, you will begin to create data visualizations in Python. You will do this by exploring the array of visual tools available in Matplotlib, a Python package designed with straightforward code techniques to make effective visualizations of data sets. You'll start by examining visualization libraries to determine the styles that best meet the needs of your data. You will then examine some simple approaches to efficiently utilize the Matplotlib documentation. Finally, you will create several plot types in Python, applying best practices and design principles in order to clearly and accurately communicate the story contained in your data. At the end of this course, you will be able to create and customize your own visualizations with minimal programming experience required.
Key Course Takeaways
- Use Python-based Matplotlib to create a basic plot
- Use Python to customize several different plot types, including advanced subplot visualizations
- Apply visualization best practices to your plot to clearly and accurately communicate your data
How It Works
3-5 hours per week
100% online, instructor-led
Who Should Enroll
- Data scientists
- Business analysts
- Technical and engineering leaders