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

Quarter: Spring
Day(s): Tuesdays
Course Format: On-campus
Duration: 5 weeks
Date(s): Apr 24—May 22
Time: 7:00—8:50 pm
Drop Deadline: May 7
Unit: 1
Tuition: $355
Instructor(s): Ronjon Nag, Sohila Zadran
Status: Open
7:00—8:50 pm
Apr 24—May 22
5 weeks
Drop By
May 7
1 Unit
Ronjon Nag, Sohila Zadran
Artificial intelligence (AI) is inspired by our understanding 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 from how the brain works, and we will 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, students should have enough basic understanding of how AI techniques work so they can: (A) converse with neural network practitioners and company executives; (B) 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.

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, where he received a PhD in engineering, at Stanford, where he was a Harkness Fellow; and at MIT, where he received an MS. In 2014, he received the Mountbatten Medal from the Institution of Engineering and Technology for his contributions to the modern mobile phone industry with the development of smartphone components such as text and speech recognition and mobile app stores, which were later incorporated widely into early smartphones. Companies he has co-founded or advised have been sold to Motorola, BlackBerry, and Apple.

Sohila Zadran, Neuroscientist

Sohila Zadran received a PhD in neuroscience from USC and was a postdoctoral fellow at Caltech. By the age of 30, she founded four biotech companies and currently serves as an advisor to several companies and to accelerators including Skydeck and qb3. She has also worked for various Silicon Valley venture capital firms and recently joined Khosla Ventures.

Textbooks for this course:

(Required) Tariq Rashid, Make Your Own Neural Network (ISBN 978-1530826605)