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SCI 52 — Artificial Intelligence: Deep Learning, Human-Centered AI, and Beyond

Quarter: Fall
Day(s): Tuesdays
Course Format: On-campus
Duration: 8 weeks
Date(s): Oct 8—Dec 3
Time: 7:00—9:00 pm
Drop Deadline: Oct 21
Unit: 1
Tuition: $455
Instructor(s): Ronjon Nag
Status: Open
Please Note: No class on November 26
Fall
On-campus
Tuesdays
7:00—9:00 pm
Date(s)
Oct 8—Dec 3
8 weeks
Drop By
Oct 21
1 Unit
Fees
$455
Instructor(s):
Ronjon Nag
Open
Please Note: No class on November 26
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 provide an introductory overview of these artificial intelligence techniques. Additionally, we will inspect what is beyond deep learning as humans participate in a human-centered AI world. Through pre-built 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. We will also discuss the real-world applications of 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 with current neural network models.

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 Distinguished Careers Institute; Fellow, Stanford Center for the Study of Language and Information

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 Mountbatten Medal from the Royal Institution of Engineering and Technology, and 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 978-1530826605)
DOWNLOAD THE PRELIMINARY SYLLABUS » (subject to change)