ENSF611
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Machine Learning for Software Engineers
Subject
ENSF - Software Engineering for Engineers
Description
Covers Machine Learning, which focuses on developing machine learning applications, specifically in the engineering domain. Covers basic techniques for supervised and unsupervised learning, with the emphasis on the applied aspects of the techniques.
Prerequisite(s): Admission to the MEng with specialization in Software Engineering and completion of Software Engineering for Engineers 692, 693 and 694; or admission to the MEng with specialization in Software Engineering, foundation courses exempt cohort.
Antirequisite(s): Credit for Software Engineering for Engineers 611 and either 519.47 (Applied Data Science) or 619.25 (Machine Learning for ENSF) will not be allowed.
Prerequisite(s): Admission to the MEng with specialization in Software Engineering and completion of Software Engineering for Engineers 692, 693 and 694; or admission to the MEng with specialization in Software Engineering, foundation courses exempt cohort.
Antirequisite(s): Credit for Software Engineering for Engineers 611 and either 519.47 (Applied Data Science) or 619.25 (Machine Learning for ENSF) will not be allowed.
Course Attributes
Fee Rate Group(Domestic) - B, Fee Rate Group(International) -D, 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
ENSF