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SCI 52 — Introduction to Artificial Intelligence and Beyond

Quarter: Fall
Day(s): Saturdays
Course Format: Live Online (About Formats)
Duration: 7 weeks
Date(s): Oct 1—Nov 12
Time: 8:30—10:30 am (PT) 
Refund Deadline: Oct 3
Unit: 1
Tuition: $460
Instructor(s): Ronjon Nag
Class Recording Available: Yes
Status: Registration opens Aug 22, 8:30 am (PT)
 
Fall
Live Online(About Formats)
Saturdays
8:30—10:30 am (PT) 
Date(s)
Oct 1—Nov 12
7 weeks
Refund Date
Oct 3
1 Unit
Fees
$460
Instructor(s):
Ronjon Nag
Recording
Yes
Registration opens Aug 22, 8:30 am (PT)
Artificial intelligence (AI) is inspired by our understanding of how the human brain learns and processes information and has given rise to powerful techniques known as neural networks and deep learning. This course will begin with an introductory overview of these AI techniques. We then will inspect what is beyond deep learning and real-world applications of neural networks, as well as implications to society as people participate in a human-centered AI world. Through hands-on exercises, we will discover how current AI platforms compare with how the brain works, how systems actually “learn,” and how to build and apply neural networks. By the end of the course, students will have a greater understanding of neural networks and deep learning 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.

This introductory course is open to students of all levels. No computer science or programming experience is needed, but an understanding of simple algebra is expected.

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

Ronjon Nag has invented AI systems for three decades. He has started companies sold to Motorola, BlackBerry, and Apple. In 2016, he became a Stanford Interdisciplinary Distinguished Careers Institute Fellow. He received a PhD in engineering from Cambridge. He won the IET Mountbatten Medal, the $1M Verizon Prize for Bounce Imaging, and the 2021 IEEE-SCV Outstanding Engineer Award.