Artificial intelligence (AI), inspired by our understanding of how the human brain learns and processes information, has given rise to powerful techniques known as neural networks and deep learning. This course will provide a high-level overview of these and other artificial intelligence techniques. Through pre-built hands-on exercises, we will discuss 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 societal and ethical issues surrounding the real-world applications of neural networks. By the end of the course, students will understand how AI techniques work 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 course is ideal for product managers who interact with data scientists, software engineers who wish for more AI exposure, and anyone in the general public who wants to know how current AI works.

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No computer science or programming experience is needed, but an understanding of simple algebra is expected.

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Instructor: Prof. Ronjon Nag
Adjunct Professor in Genetics, Stanford School of Medicine; Visiting Fellow, Stanford Center for Study of Language and Information; President, R42 Group

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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.