IAI 5101 Foundations of Machine Learning for Scientists and Engineers

3 units
Interdisciplinary Artificial Intelligence
Faculty of Engineering
The capabilities and limitations of machine learning; problem formulation and requirement engineering; supervised and unsupervised learning techniques; designing, deploying, monitoring and evaluating machine learning models; assessing the results of learning; current advances in application areas such as engineering, science and health. Recommended prerequisite: No specific programming required, students should have taken an introduction to programming at the undergraduate level as well as linear algebra I & calculus II.

Components:

Lecture

Requirements:

Courses CSI 5155 , DTO 5100 , DTO 5101 , ELG 5255 , IAI 5100 , IAI 5101 , MIA 5100 , SYS 5185 cannot be combined for units.

Previously Offered Terms:

Winter

Organized

45 responses

4.58

/ 5

strongly agree
71%
agree
22%
neither agree nor disagree
2%
disagree
2%
strongly disagree
2%
25%
50%
75%
100%

Clear Expectations

45 responses

4.62

/ 5

strongly agree
73%
agree
22%
neither agree nor disagree
0%
disagree
2%
strongly disagree
2%
25%
50%
75%
100%

Learned a Lot

45 responses

4.58

/ 5

strongly agree
67%
agree
29%
neither agree nor disagree
2%
disagree
0%
strongly disagree
2%
25%
50%
75%
100%

Fair Assessments

45 responses

4.71

/ 5

strongly agree
80%
agree
13%
neither agree nor disagree
4%
disagree
2%
strongly disagree
0%
25%
50%
75%
100%