18-662   Principles and Engineering Applications of AI

Location: Pittsburgh

Units: 12

Semester Offered: Spring

Course description

The course will review the basic principles of AI. Some of the specific topics that will be covered are the following:

  • Intelligent Agents
  • Single-Agents and Multi-Agent Systems (MAS)
  • Uncertain Knowledge and Reasoning (Probabilistic Reasoning and Probabilistic Reasoning over Time, Bayesian Networks, Dynamic Bayesian Networks, Hidden Markov Models, Kalman Filters, MCMC algorithms, etc.)
  • Learning
  • Communicating, Perceiving, and Acting
  • Robotics

The course will involve completing a set of challenging engineering applications of AI that will include: medical applications, video games, autonomous driving, autonomous robots, finance and economics, military, art, and advertising. Students should have a good background in basic probability theory, maturity in mathematical topics, and good programming skills. permission will be required.

See the original course description for the most recent information.


18-751 Applied Stochastic Processes with a minimum grade of B.

For seniors who would like to take the course but do not have the necessary prerequisites, instructor’s


Ozan Tonguz and Ahmed Biyabani