Syllabus & Course Structure

This section covers the syllabus structure and course materials for Data 6: Introduction to Computational Thinking with Data Science and Society.

Course Overview¶

Data 6 is an introductory, interdisciplinary course that focuses on the principles of computational thinking for the purposes of exploratory data analysis and computational social science. The course combines programming skills with statistical concepts and social science applications.

Course Materials¶

The course materials include:

• Lecture slides: Available through the course website at data6.org

• Course notes: Online lecture notes available at data6.org/notes

• Public student materials: Jupyter notebooks for labs, homeworks, and projects available at https://github.com/dubois-ctds/data-6-materials-student

• Foundational texts: Links to foundational texts from Data 8, CS 61A, and Stat 20 are provided within the course notes

Course Structure¶

The course is typically structured around weekly topics, with:

• Two lectures per week

• One lab section per week

• Homework assignments

• Midterm and final exams

• Three projects

For more specific information about the syllabus structure, please refer to the course website at data6.org.