This page contains a collection of resources for professors to use in adopting data science curricula at their own institutions. These resources have been prepared through a collaborative effort with the Data Science Education Program (DSEP) and the professors of the Department of Statistics, Computer Science, faculty in Human Contexts and Ethics, and more.
Several of the institutions we have worked with in the past are listed on our partner institutions page.
Data 8 is a foundational data science course combining three perspectives: inferential thinking, computational thinking, and real-world relevance. Find information on the Data 8 course website, textbook, and further resources related to adopting the course here.
Instructor Interest Form - Interested in adopting Data 8 curriculum? Complete our interest form!
Data 100 is an intermediate level class that explores key areas of data science including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision making. Read more about Data 100 goals, course materials, website, textbook, and adoption guide here.
Browse guides on adopting and developing courses related to the data science major and/or minor, as well as related programs such as Human Contexts and Ethics (HCE). Other information relevant to instructors teaching modules and connectors can also be found.
Overview two major infrastructural accessories - JupyterHub and Otter Grader - essential for teaching data science courses at scale. Deployment guides and community forums are linked to assist instructors in shaping their courses with the right services.
The California Alliance for Data Science Education (CADSE) seeks to advance data science education in California Community Colleges (CCCs), California State Universities, and the University of California system. Read more about CADSE success stories and initiatives expanding across the state.