The following courses can satisfy the Reasoning Core Area Breadth Requirement for the Robotics MS/PhD program:
- AEROSP 552: Aerospace Information Systems
- AEROSP 575: Flight & Trajectory Optimization
- AEROSP 584: Avionics, Navigation & Guidance of Aerospace Vehicles
- AEROSP 584: Navigation & Guidance of Aerospace Vehicles
- AEROSP 729/NERS 590/MECHENG 599: Machine Learning for Science
- EECS 453: Principles of Machine Learning - *credit only if taken before EECS 545 and EECS 553 and only one of EECS 453 OR EECS 545 OR EECS 553 can count toward the Robotics MS and/or PhD
- EECS 486: Information Retrieval & Web Search
- EECS 505: Computational Data Science and Machine Learning
- EECS 542: Advanced Topics in Computer Vision
- EECS 543: Knowledge-Based Systems
- EECS 545: Machine Learning - *only one of EECS 453 OR EECS 545 OR EECS 553 can count toward the Robotics MS and/or PhD
- EECS 548: Information Visualization
- EECS 549 / SI 650: Information Retrieval
- EECS 550: Information Theory
- EECS 553: Machine Learning (ECE) - *only one of EECS 453 OR EECS 545 OR EECS 553 can count toward the Robotics MS and/or PhD
- EECS 558: Stochastic Control
- EECS 559: Optimization for Signal Processing and Machine Learning
- EECS 563: Hybrid Systems: Specification, Verification, & Control
- EECS 572: Randomness and Computation
- EECS 576: Advanced Data Mining
- EECS 592: Foundations of Artificial Intelligence
- EECS 595/LING 541/SI 561: Natural Language Processing
- EECS 602: Reinforcement Learning Theory (Ying)
- EECS 692: Advanced Artificial Intelligence
- IOE 434: Human Error and Complex System Failures
- IOE 465: Design and Analysis of Experiments
- IOE 511: Continuous Optimization Methods
- IOE 512: Dynamic Programming
- IOE 536: Cognitive Ergonomics and Human System Integration
- IOE 560: Bayesian Data Analysis
- IOE 562: Reliability
- IOE 611: Nonlinear Programming
- IOE 691: Approximation Algorithms
- MATH 525: Probability Theory
- MECHENG 555: Design Optimization
- ROB 422/EECS465: Introduction to Algorithmic Robotics
- ROB 511: Robot Operating Systems
- ROB 520 (formerly EECS 598): Motion Planning
- ROB 543: Ethics in AI & Robotics
- ROB 599: Deep Learning for Robot Perception
- ROB 599: Multi-Robot Systems
Special Topics Courses:
- CSE 598.006 Causality and Machine Learning
- EECS 498: Principles of Machine Learning - *credit only if taken before EECS 453, EECS 545, and EECS 553
- EECS 498: Machine Learning Basics for Engineering Applications * credit only if taken before EECS 453, EECS 545 and EECS 553
- EECS 598: Reinforcement Learning *Seating is extremely limited. Consider alternate courses.
- EECS 598: Computational Data Science
- EECS 598: Computational Modeling in Human-Computer Interaction
- EECS 598: Situated Language Processing for Embodied AI Agents
- EECS 598: Formal Verification
- EECS 598: Approximation Algorithms
- EECS 598: Foundations of Large Language Models
- EECS 598: Machine Learning Theory
- EECS 598: Computer Graphics and GenModels