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TECH 152 — A Crash Course in AI

Quarter: Fall
Day(s): Mondays
Course Format: Live Online (About Formats)
Duration: 5 weeks
Date(s): Oct 16—Nov 13
Time: 7:00—9:00 pm (PT)
Refund Deadline: Oct 18
Unit: 1
Tuition: $425
Instructor(s): Ronjon Nag
Class Recording Available: Yes
Status: Open
ACCESS THE SYLLABUS » (subject to change)
Live Online(About Formats)
7:00—9:00 pm (PT)
Oct 16—Nov 13
5 weeks
Refund Date
Oct 18
1 Unit
Ronjon Nag
ACCESS THE SYLLABUS » (subject to change)
Artificial intelligence (AI) is in the news daily. This course will provide a high-level overview of AI techniques. Through pre-built hands-on exercises, we will discuss how current AI platforms compare with how the brain works and how AI systems actually “learn.” Specifically, we will cover neural networks and their applicability to generative AI and large language models. We will also discuss the societal and ethical issues surrounding the real-world applications of AI. By the end of the course, students will understand how AI techniques work so they can (1) converse with AI practitioners and companies; (2) be able to critically evaluate AI news stories and technologies; and (3) consider what the future of AI can hold and what barriers need to be overcome with current AI models. This course is ideal for product managers who interact with data scientists, software engineers who wish for more AI exposure, and anyone in the general public who wants to know how current AI works.

No computer science or programming experience is needed, but an understanding of simple algebra is expected.

Adjunct Professor in Genetics, Stanford School of Medicine; Visiting Fellow, Stanford Center for the Study of Language and Information; President, R42 Group

Ronjon Nag has been building AI systems for 40 years and sold companies he co-founded or advised to Motorola, RIM/Blackberry, and Apple. He is a venture capitalist with his firm R42, which invests in AI and longevity companies. He became a Stanford Interdisciplinary Distinguished Careers Institute Fellow in 2016. He teaches AI, genes, and ethics courses at the Stanford School of Medicine. Nag received a PhD from Cambridge, an MS from MIT, the IET Mountbatten Medal, the $1 million Verizon Powerful Answers Award, and the 2021 IEEE-SCV Outstanding Engineer Award. He is co-founder and part owner of some 100 AI and biotech startups.

Textbooks for this course:

(Required) Tariq Rashid, Make Your Own Neural Network (ISBN 978-1530826605)