CS109b: Advanced Topics in Data Science

Spring 2022

Pavlos Protopapas & Mark Glickman

Advanced Topics in Data Science (CS109b) is the second half of a one-year introduction to data science. Building upon the material in Introduction to Data Science, the course introduces advanced methods for data wrangling, data visualization, statistical modeling, and prediction. Topics include big data, multiple deep learning architectures such as CNNs, RNNs, transformers, language models, autoencoders, and generative models as well as basic Bayesian methods, and unsupervised learning.

Helpline: cs109b2022@gmail.com

Lectures: Mon & Wed 9:45‐11 am
Labs: Fri 9:45-11 am
Advanced Sections: Weds 2:15-3:30 pm (see schedule for specific dates)
Office Hours: See Ed Post
Course material can be viewed in the public GitHub repository.

Previous Material