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SCI 52 — An Introduction to Artificial Intelligence and Beyond

Quarter: Summer
Day(s): Wednesdays
Course Format: Live Online (About Formats)
Duration: 9 weeks
Date(s): Jun 30—Aug 25
Time: 7:00—9:00 pm (PT)
Refund Deadline: Jul 2
Unit: 1
Tuition: $520
Instructor(s): Ronjon Nag
Class Recording Available: Yes
Status: Registration opens May 17, 8:30 am (PT)
 
DOWNLOAD THE SYLLABUS » (subject to change)
Summer
Live Online(About Formats)
Wednesdays
7:00—9:00 pm (PT)
Date(s)
Jun 30—Aug 25
9 weeks
Refund Date
Jul 2
1 Unit
Fees
$520
Instructor(s):
Ronjon Nag
Recording
Yes
Registration opens May 17, 8:30 am (PT)
DOWNLOAD THE SYLLABUS » (subject to change)
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) 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.

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
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. He received a PhD in engineering from Cambridge, an MS from MIT, and the IET Mountbatten Medal at The Royal Institution. He is a Stanford Interdisciplinary Distinguished Careers Institute Fellow. 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)