276.23S sec. 001 - Fundamentals of AI Technology (Summer 2026)
Instructor: Brandie Nonnecke (view instructor's teaching evaluations - degree students only)
View all teaching evaluations for this course - degree students only
Units: 2
Grading Designation: Graded
Mode of Instruction: In-Person
Meeting:
MTuWThF 2:00 PM - 4:35 PM
Location: Law 132
From June 02, 2026
To June 15, 2026
Enrollment info:
Enrolled: 10
Waitlisted: 0
Enroll Limit: 30
As of: 04/13 03:53 AM
Taught by AI governance expert Brandie Nonnecke, PhD, this course provides lawyers with a foundational understanding of artificial intelligence and machine learning, covering the continuum from narrow AI to the theoretical frontier of strong AI. Learners will explore the essential types of machine learning—including supervised and unsupervised learning, reinforcement learning, and deep learning—gaining insights into how these technologies operate, their real-world applications, and the legal implications that come with their use. This course is designed to demystify AI concepts, empowering legal professionals to engage knowledgeably with AI-related cases, policies, and ethical considerations.
Brandie Nonnecke, PhD is Senior Director of Policy at Americans for Responsible Innovation. She was the Founding Director of the CITRIS Policy Lab, headquartered at UC Berkeley. She served as an associate research professor at the Goldman School of Public Policy (GSPP) and as a faculty co-director at the Berkeley Center for Law and Technology at Berkeley Law. Her research has been featured in Science, Wired, NPR, BBC News, MIT Technology Review, Buzzfeed News, among others. Brandie received the SF Business Times INSPIRE Award for her leadership in AI in 2024 and was named one of the 100 Brilliant Women in AI Ethics in 2021.
Exam Notes: (P) Final Paper
(Subject to change by faculty member only through the first two weeks of instruction)
Course Category: Intellectual Property and Technology Law
This course is listed in the following sub-categories:
AI Law and Regulation
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