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TECH 152 H — A Crash Course in AI

Quarter: Spring
Day(s): Mondays
Course Format: On-campus (About Formats)
Duration: 6 weeks
Date(s): Apr 22—Jun 3
Time: 7:00—9:00 pm (PT)
Refund Deadline: Apr 24
Unit: 1
Tuition: $485
Instructor(s): Ronjon Nag, Artem A. Trotsyuk
Class Recording Available: Yes
Status: Open
Please Note: No class on May 27
ACCESS THE SYLLABUS » (subject to change)
7:00—9:00 pm (PT)
Apr 22—Jun 3
6 weeks
Refund Date
Apr 24
1 Unit
Ronjon Nag, Artem A. Trotsyuk
Please Note: No class on May 27
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.

This course introduces foundational machine learning principles. While previous experience isn't required to take the course, those with a STEM background may have less difficulty with its technical concepts. Students can choose to attend this course on campus or online. Sign up for Section H if you think you might attend class on the Stanford campus at least once. There is no commitment—you can still choose to attend via Zoom for any session. Sign up for Section Z if you know you will exclusively attend via Zoom.

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 co-founded or advised companies sold 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 Stanford Medicine. He 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. Nag is the 2024 inductee in the Silicon Valley Engineering Hall of Fame. He is part owner of some 100 AI and biotech startups.

GSK.ai Ethics Fellow, Stanford Center for Biomedical Ethics, Stanford School of Medicine

Artem A. Trotsyuk teaches longevity science and biotech venture capital courses at the Stanford School of Medicine and School of Engineering. As an AI Ethics Fellow at Stanford, he looks at the dual use implications of AI in biomedical research. He is involved in the entrepreneurship ecosystem both at Stanford and in the Bay Area. He advises early-stage founders on navigating the complexities of startup formation and fundraising milestones. Trotsyuk received a PhD in bioengineering and artificial intelligence and an MS in computer science from Stanford.

Textbooks for this course:

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