All courses offered in Fall 2022 will be delivered in-person (unless historically offered online).
For delivery method and date and time of offer please look at the schedule of classes.
Instructor |
Recommended Background |
Area |
Course Number |
Course Title |
Jesse Hoey |
Artificial Intelligence (https://cs.uwaterloo.ca/current-graduate-students/courses/non-cs-courses-and-special-topic-courses-approved-course) |
COGSCI 600 | Cognitive Science | |
Prabhakar Radge | This course is only for STAT graduate students in the MDSAI program. | CS 600 | Fundamentals of Computer Science for Data Science | |
Dan Holtby | CS 631 | Data-Intensive Dist. Analytics | ||
Tamer Ozsu | CS 638 | Principles of Data Mgmt & Use | ||
Joanne Atlee | Software Engineering | CS 645 | Software Req Specif & Analysis | |
Daniel Vogel | Graphics and User Interfaces | CS 649 | Human-Computer Interaction | |
Dan Holtby | Hardware and Software Systems | CS 651 | Data-Intensive Distrib Computing | |
Martin Karsten | Hardware and Software Systems | CS 652 | Real-Time Programming | |
Khuzaima Daudjee | Hardware and Software Systems | CS 654 | Distributed Systems | |
Samer Al Kiswany | Hardware and Software Systems | CS 656 | Computer Networks | |
Yousra Aafer & Simon Oya Diez | Hardware and Software Systems | CS 658 | Computer Security and Privacy | |
Therese Biedl & Rafael Oliveira | Algorithms and Complexity | CS 666 | Algorithm Design & Analysis | |
Yaoliang Yu | Computational Statistics | CS 680 | Intro to Machine Learning | |
Yuri Boykov | Artificial Intelligence | CS 684 | Computational Vision | |
Shai Ben-David | Computational Statistics | CS 685 | Machine Learning | |
Blake Paul Allen Vanberlo | Artificial Intelligence | CS 686 | Intro Artificial Intelligence | |
Stephan Mann | Graphics and User Interfaces | CS 688 | Intro to Computer Graphics | |
Anna Lubiw | Algorithms and Complexity | CS 763 | Computational Geometry | |
Richard Cleve | Quantum Information and Computation | CS 768 | Quantum Information Processing | |
Hans De Sterck | Scientific and Symbolic Computing | CS 770 | Numerical Analysis | |
Yaoliang Yu |
Linear algebra; some prior exposure to optimization and machine learning would be great. |
Computational Statistics or Scientific and Symbolic Computing | CS 794 | Optimization for Data Science |
Walaa Moursi | Algorithms and Complexity | CS 795 | Fundamentals of Optimization | |
Mostafa Ammar | A previous introductory networking course which could have been taken anywhere and does not have to be recent | Hardware and Software Systems | CS 798 |
Advanced Research Topics: Modern Network Protocols and Applications |
Stephen Watt | Taken an undergraduate course in programming languages or compiler design | Programming Languages | CS 842 | Advanced Topics in Language Design and Implementation |
Chengnian Sun | Software Engineering | CS 846 | Advanced Topics in Software Testing and Debug | |
Paulo Alencar | Software Engineering | CS 846 |
Software Engineering for Big Data & AI |
|
Jimmy Lin | Databases | CS 848 | Art & Science of Empirical CS | |
Semih Salihoglu | Databases | CS 848 | Knowledge Graphs | |
Tim Brecht | Hardware and Software Systems | CS 854 | Advanced Topic in Computer Systems | |
Urs Hengartner |
Hardware and Software Systems |
CS 858 |
User Authentication |
|
Meng Xu | Open background | Hardware and Software Systems | CS 858 |
Offensive and Defensive Approaches to Software Security |
Hongyang Zhang |
An undergraduate-level knowledge on machine learning and optimization |
Algorithms and Complexity | CS 858 | Security and Privacy of Machine Learning |
Gautam C. Kamath | An undergraduate understanding of algorithms, comfort with probability, and mathematical maturity | Algorithms and Complexity | CS 860 | Algorithms-Privt Data Analysis (#33) |
Rafael Oliveira | Algorithms and Complexity | CS 860 | Computational Complexity Theory | |
Pascal Poupart |
Computational Statistics |
CS 885 |
Reinforcement Learning |