CO 673Optimization for Data Science
- Units
- 0.50
- Level
- Graduate
- Faculty
- Mathematics
- Cross-listed
- CS 794
CO 673 as listed in the Spring 2026 Graduate Calendar. The main page has the current version, when it runs, and seats.
Techniques for formulating data science models as optimization problems. Algorithms for solving data science problems with an emphasis on scalability, efficiency and parallelizability including gradient-descent based algorithms, derivative-free algorithms, and randomized algorithms. Theoretical analyses of algorithms and approaches for recognizing the most suitable algorithm for solving a particular problem.
Prerequisites
None listed.
Antirequisites
None listed.
Leads to
No course lists it as a requisite.
Check it elsewhere for Spring 2026
- Graduate Calendar, Spring 2026The archived entry
- Requirements for Spring 2026Waterloo’s requisite checker
- Schedule of Classes, Spring 2026Instructors, rooms, live seats
- Quest Class SearchWhere you enrol
- Course outlinesSyllabi from past terms (UW login)
- UW FlowStudent ratings and reviews
- WClassesPast sections back to 2004, and who taught them