WSP 152 — A Crash Course in Artificial Intelligence
Course Format: Virtual
Duration: 4 weeks
Date(s): Jun 29—Jul 20
Time: 7:00—8:45 pm (PT)
Drop Deadline: Jul 5
Grade Restriction: NGR only; no credit/letter grade
Instructor(s): Ronjon Nag
7:00—8:45 pm (PT)
Jun 29—Jul 20
NGR only; no credit/letter grade
Everything you wanted to know about artificial intelligence (AI) but were afraid to ask! 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 workshop 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) 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 workshop 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.
Ronjon Nag, Interdisciplinary Fellow, Stanford Distinguished Careers Institute; Fellow, Stanford Center for the Study of Language and Information; Founder and Managing Partner, R42 GroupRonjon Nag has invented and deployed artificial intelligence systems for over three decades. He received a PhD in engineering from Cambridge, an MS from MIT, and the IET Mountbatten Medal, and he was a Harkness Fellow at Stanford. Companies he has co-founded or advised have been sold to Motorola, BlackBerry, and Apple.
Textbooks for this course:
(Required) Tariq Rashid, Make Your Own Neural Network (ISBN 1530826608)