Introduction to Artificial Intelligence

AI-Class

The objective of this class is to teach you modern AI. You will learn about the basic techniques and tricks of the trade. We also aspire to excite you…

Class Summary

The objective of this class is to teach you modern AI. You will learn about the basic techniques and tricks of the trade. We also aspire to excite you about the field of AI.

What Should I Know?

Some of the topics in Introduction to Artificial Intelligence will build on probability theory and linear algebra. You should have understanding of probability theory comparable to that at our ST101: Introduction to Statistics class

What Will I Learn?

This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing.

Syllabus

Overview of AI

Statistics, Uncertainty, and Bayes networks

Machine Learning

Logic and Planning

Markov Decision Processes and Reinforcement Learning

Hidden Markov Models and Filters

Adversarial and Advanced Planning

Image Processing and Computer Vision

Robotics and robot motion planning

Natural Language Processing and Information Retrieval

Course Instructors

Sebastian Thrun is a Research Professor of Computer Science at Stanford University, a Google Fellow, a member of the National Academy of Engineering and the German Academy of Sciences. Thrun is best known for his research in robotics and machine learning, specifically his work with self-driving cars.

Peter Norvig is Director of Research at Google Inc. He is also a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Norvig is co-author of the popular textbook Artificial Intelligence: A Modern Approach. Prior to joining Google he was the head of the Computation Sciences Division at NASA Ames Research Center.