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DATA433

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Essential Optimization

Mathematics and Statistics SC - Faculty of Science

Subject

DATA - Data Science

Description

Unconstrained optimization and constrained optimization. Linear programing. Graph algorithms (including shortest-path and min-cut/max-flow) and integer programming. Simulated annealing and evolutionary algorithms. Other aspects of optimization as time permits.

Prerequisite(s): Computer Science 217, Mathematics 267 and 311.

Course Attributes

Fee Rate Group(Domestic) - A, Fee Rate Group(International) -A, GFC Hours (3-2)

Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.

Component

LAB

Component

LEC

Units

3

Repeat for Credit

No

Subject code

DATA

Understanding Course Information

Please refer to Course Terminology and Description to better understand how to interpret course information such as GFC hours, prerequisites, course levels, etc.
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