The AI Specialization is available for Bachelor of Computer Science (BCS), Bachelor of Mathematics (BMath) (Computer Science), and Bachelor of Software Engineering (BSE) academic plans. Students in BCS Data Science are not eligible for this specialization. The requirements are the same as for the BCS and BMath Computer Science (CS) and BSE academic plans with the following additional requirements:
- All of
- CS 486 Introduction to Artificial Intelligence
- CS 492 The Social Implications of Computing
- CS 480 Introduction to Machine Learning or CS 485 Statistical and Computational Foundations of Machine Learning
- Four additional courses, one of which must be from Mathematics and one from Engineering, from
- CO 367 Nonlinear Optimization
- CO 456 Introduction to Game Theory
- CO 463 Convex Optimization and Analysis
- CO 466 Continuous Optimization
- CS 452 Real-time Programming
- CS 479 Neural Networks
- CS 480 Introduction to Machine Learning
- CS 484 Computational Vision
- CS 485 Statistical and Computational Foundations of Machine Learning
- STAT 341 Computational Statistics and Data Analysis
- STAT 440 Computational Inference
- STAT 441 Statistical Learning - Classification
- STAT 444 Statistical Learning - Advanced Regression
- ECE 380 Analog Control Systems or SE 380 Introduction to Feedback Control
- ECE 423 Embedded Computer Systems
- ECE 457C Reinforcement Learning
- ECE 481 Digital Control Systems
- ECE 486 Robot Dynamics and Control
- ECE 488 Multivariable Control Systems
- ECE 495 Autonomous Vehicles
- MTE 544 Autonomous Mobile Robots
- SYDE 552/BIOL 487 Computational Neuroscience
- SYDE 556 Simulating Neurobiological Systems
- SYDE 572 Introduction to Pattern Recognition
Note
CS 497 may be substituted for CS 492, depending on the topic of the course.