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SCI 52 — Artificial Intelligence: An Introduction to Neural Networks and Deep Learning

Quarter: Winter
Day(s): Tuesdays
Course Format: On-campus course
Duration: 5 weeks
Date(s): Jan 23—Feb 27
Time: 7:00—8:50 pm
Drop Deadline: Feb 5
Unit: 1
Tuition: $355
Instructor(s): Ronjon Nag, Sohila Zadran
Status: Registration opens on 12/04/2017
Please Note: No class on February 20
Winter
On-campus course
Tuesdays
7:00—8:50 pm
Date(s)
Jan 23—Feb 27
5 weeks
Drop By
Feb 5
1 Unit
Fees
$355
Instructor(s):
Ronjon Nag, Sohila Zadran
Registration opens on 12/04/2017
Please Note: No class on February 20
Artificial intelligence (AI) is inspired by our understandings of how the human brain learns and processes information and has given rise to powerful AI techniques known as neural networks and deep learning. Much of deep learning in artificial intelligence uses the neuron, the cellular unit of the brain, as its biological inspiration.

This course will provide an introductory overview of artificial intelligence techniques and place a particular emphasis on neural networks and deep learning. We will discuss how current AI platforms compare and differ with how the brain works, and cover how systems actually “learn” and how to build a neural network. We will also discuss the real-world applications of neural networks. By the end of the course, the aim is for students to have a good intuition of how AI techniques work so as to be able to: A) converse with neural network practitioners and companies; B) be able to critically evaluate AI news stories and technologies; and C) 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 middle-school math (e.g., simple algebra) is expected, with any further material covered in class.

Students are not required to complete SCI 48: "An Introduction to Artificial Intelligence: How Neuroscience Is Creating Smarter Technologies" prior to this course. However, prospective students should review both syllabi to determine which course best suits their needs. SCI 48 is also offered this Winter.

Ronjon Nag, Fellow, Stanford Distinguished Careers Institute

Ronjon Nag has deployed artificial intelligence systems for mobile devices over three decades, working on neural networks at Cambridge, MIT, and Stanford. As a Harkness Fellow, he received an MS from MIT and studied neural networks in Stanford's Department of Psychology. In 2014, Nag was the recipient of the Mountbatten Medal awarded at the Royal Institution. The award cited Nag's influence on the creation of the modern mobile phone industry with the development of smartphone components such as text and speech recognition and mobile app stores, technologies that were later incorporated widely into early smartphones. The companies he has co-founded or advised have been sold to Motorola, BlackBerry, and Apple. He is chairman of Embee Mobile, Brightswitch, and an advisor to numerous high-tech companies. He received a PhD from Cambridge.

Sohila Zadran, Founder, Igantia Therapeutics

Sohila Zadran’s research concerns genomics and understanding aging in the brain. She received a PhD in neuroscience from USC and was a postdoctoral fellow in systems neuroscience at the California Institute of Technology. She is on the board of directors for NeuroSwitchBoard.

Textbooks for this course:

(Recommended) Mark Smart, Neural Networks for Complete Beginners: Introduction for Neural Network Programming (ISBN 978-1543268720)
(Recommended) Tariq Rashid , Make Your Own Neural Network (ISBN 978-1530826605)