This version of the guide is outdated- please see the most recent version at https://berkeley-data.gitbook.io/curriculum-guide/

Welcome to the UC Berkeley Data Science Curriculum Guide!

What is this guide and who is it for?

The information in the guide is primarily intended for instructors who either currently are or will be teaching a course in the UC Berkeley Data Science Education Program: either a connector course, a data-enabled course, or a course featuring a data science module. However, anyone else who wants to learn more about the program, the courses, and the technology is encouraged to look through the guide.

How should I use this guide?

The information is divided up into six sections:

  1. Introduction: An overview of the different Data Science Education course types and technology
  2. Creating a Connector: A guide to the pre-course set-up for a Connector course
  3. Making a Module: A guide to the pre-course set-up for a Module
  4. Workflow Basics: Helpful information around creating, distributing, and grading assignments
  5. During The Course: Guides to frequent issues that pop up during data science courses
  6. Reference: Useful people, terms, and contact information to know.

The first time you read through the material, you might go through the topics in order. After the first read, you could refer back to specific sections when seeking answers to questions.

Not able to find what you are looking for?

Try using the search bar at the top right of the page!

If you still have questions or concerns that are not addressed in this guide, you can post on the connector instructor Piazza site. This site is monitored by DSEP staff and we will get back to you promptly with a response.

You can also email your questions to the DSEP Curriculum Coordinator, Ryan Edwards.

results matching ""

    No results matching ""