CS 06 — Introduction to Data Visualization with Python
Day(s): Saturday and Sunday
Course Format: On-campus (About Formats)
Duration: 2 days
Date(s): Apr 15—Apr 16
Time: 10:00 am—4:00 pm (PT)
Refund Deadline: Apr 8
Instructor(s): Charlie Flanagan
Class Recording Available: No
Saturday and Sunday
10:00 am—4:00 pm (PT)
Apr 15—Apr 16
In today’s world, being able to tell a story with data is essential. This course will teach students how to create and publish stunning data visualizations and interactive graphics using the latest open source tools. We will begin with an introduction to loading and preprocessing data using Python and SQL. We will survey the ecosystem of visualization tools, explaining the pros and cons of each, reviewing the different visualization chart types, and discussing what each is best at conveying. We will then move to creating visualizations using popular open source libraries such as matplotlib and seaborn. We will also try out Altair, an open source package that will allow us to build interactive and connected visualizations. The course will consist of lectures, live coding demonstrations, hands-on practice, and guest speakers who are data visualization experts from leading tech companies. We will hold lab sections each week after class so students can apply their learning to their own projects, with help from the instructor. Students will finish the course with a portfolio of visualizations that they understand deeply and can leverage going forward.
Previous basic coding experience is helpful but not required as we will be editing existing code. Students are required to bring a fully charged laptop computer to class.
Charlie Flanagan spent 10 years as a quantitative analyst in the financial industry before joining Google. He received an MS in software engineering from Harvard and an MBA from Columbia and is a chartered financial analyst (CFA).
Data Scientist, Google
Textbooks for this course:
(Recommended) Cole Nussbaumer Knaflic, Storytelling with Data: A Data Visualization Guide for Business Professionals 1st Edition (ISBN 978-1119002253)