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Course Offerings

Course Evaluation Results

Course Details

Fall 2016-2017
COS 402   Graded A-F, P/D/F, Audit

Machine Learning and Artificial Intelligence

Sanjeev Arora
Elad Hazan
Xiaoyan Li

This course will provide a basic introduction to the core principles, algorithms and techniques of modern artificial intelligence and machine learning research and practice. Main topics will include: 1. Problem solving using search, with applications to game playing 2. Probabilistic reasoning in the presence of uncertainty 3. Hidden Markov models and speech recognition 4. Markov decision processes and reinforcement learning 5. Machine learning using decision trees, neural nets and more. 6. Basic principles of mathematical optimization for learning

Sample reading list:
Russell & Norvig, AI: A Modern Approach Third Edition

Reading/Writing assignments:
Readings from textbook. Regular problem sets and programming assignments

Requirements/Grading:
Final Exam - 35%
Problem set(s) - 60%
Other (See Instructor) - 5%

Other Requirements:
Open to Juniors and Seniors Only.

Prerequisites and Restrictions:
COS 226 and COS 340.

Other information:
This course often fills up, so be sure to enroll at your earliest opportunity. Seats reserved for graduate students will be released soon after the first class.

Reserved Seats:
COS Graduate Students Only 16

Website:  http://www.cs.princeton.edu/courses/archive/fall16/cos402

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
20625 L01 11:00 am - 12:20 pm T Th   Computer Science Building   104   Enrolled:69 Limit:82