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TECH 152 — A Crash Course in Artificial Intelligence

Quarter: Summer
Day(s): Thursdays
Course Format: Live Online (About Formats)
Duration: 4 weeks
Date(s): Jul 28—Aug 18
Time: 7:00—9:00 pm (PT)
Refund Deadline: Jul 30
Unit: 0
Grade Restriction: NGR only; no credit/letter grade
Tuition: $320
Instructor(s): Ronjon Nag
Class Recording Available: Yes
Status: Open
Live Online(About Formats)
7:00—9:00 pm (PT)
Jul 28—Aug 18
4 weeks
Refund Date
Jul 30
0 Unit
Grade Restriction
NGR only; no credit/letter grade
Ronjon Nag
Artificial intelligence (AI), inspired by our understanding of how the human brain learns and processes information, has given rise to powerful techniques known as neural networks and deep learning. This course will provide a high-level overview of these and other artificial intelligence techniques. Through pre-built hands-on exercises, we will discuss how current AI platforms compare with how the brain works, how systems actually “learn,” and how to build and apply neural networks. We will also discuss the societal and ethical issues surrounding the real-world applications of neural networks. By the end of the course, students will understand how AI techniques work so they can (1) converse with neural network 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 neural network 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.

Fellow, Stanford Center for the Study of Language and Information; President, R42 Group

Ronjon Nag has invented and deployed artificial intelligence systems for over three decades. Companies he has co-founded or advised have been sold to Motorola, BlackBerry, and Apple. He received the IET Mountbatten Medal at the Royal Institution and in 2016 he became a Stanford Interdisciplinary Distinguished Careers Institute Fellow. He received a PhD in engineering from Cambridge.