DSC 140AProbabilistic Modeling and Machine Learning
The course covers learning and using probabilistic models for knowledge representation and decision-making. Topics covered include graphical models, temporal models, and online learning, as well as applications to natural language processing, adversarial learning, computational biology, and robotics. Prior completion of MATH 181A is strongly recommended.
Prerequisites
From the catalog: “DSC 80/R and (ECE 109 or ECON 120A or MAE 108 or MATH 180A or MATH 183 or MATH 186). Restricted to students with upper-division standing. Restricted to students within the DS25 major. All other students will be allowed as space permits.”
Where it sits in degree plans
Suggested plans most often put it in Year 3 · Fall (1 program).
One of the options in (2)
- Artificial Intelligence
- Data Science (B.S.)
Courses that list DSC 140A as a prerequisite (1)
- DSC 180A Data Science Project I