Data 100, Principles and Techniques of Data Science (CS/STAT C100), explores the data science lifecycle and focuses on quantitative critical thinking and key principles and techniques needed to carry out this cycle. It bridges between Foundations of Data Science (Data 8) and upper division courses.
The upper-division courses for the major together total to 30 units. Along with Computational and Inferential Depth; Probability; Modeling, Machine Learning, and Decision Making; and Human Contexts and Ethics (all detailed below), students will also select and complete a Domain Emphasis. Learn more about the Domain Emphasis requirement here.
All policies subject to finalization.
- To satisfy the requirements of the major, all courses must be taken for a letter grade and passed with a 'C-' or higher.
- Students must maintain a 'C' average in courses taken for the major, and in the upper-division courses taken for the major.
- A minimum 2.0 overall Grade Point Average is required to remain in good standing.
See details about each of the upper-division requirements and the lists of courses that satisfy each in the drop-down menus below.