Joseph E. (Joey) Gonzalez · Professor of EECS, UC Berkeley
Courses I have taught at UC Berkeley, most recent first. Each course website has the full materials for that offering.
CS 189/289A: Introduction to Machine Learning, co-taught with Narges Norouzi.
A large upper-division and graduate course covering foundational and modern machine learning, from probability, regression and optimization to neural networks, transformers and generative models. Co-taught with Narges Norouzi.
An intermediate data science course that I co-created, bridging Data 8 and upper-division courses in computer science and statistics. It covers question formulation, data cleaning, visualization, statistical inference and machine learning on real-world data, and enrolls more than 1,000 students from across campus each semester.
A graduate seminar on machine learning and AI systems research that combines paper reading, structured discussion and class projects. The Fall 2023 offering focused on large language models and the systems that support them.
Berkeley's large introductory data science course, which combines computational thinking, inferential thinking and analysis of real-world data.
An interactive seminar, created during the COVID-19 pandemic and co-hosted with Vik Singh, in which students wrote and voted on questions for live conversations with technology and venture capital leaders about their careers and the lessons they learned.
A research seminar for the newly formed RISELab, reading and discussing papers on learning systems, big data systems and systems security.
A co-taught course of more than 500 students, for which I helped update the material and created new lectures on topics where databases and data science meet.