Techniques for extracting, cleaning, and visualizing data from engineering applications. Basic numerical computation techniques underlying learning algorithms. Fundamental supervised and unsupervised learning algorithms. Emphasis will be on leveraging existing software libraries and frameworks to solve problems in various engineering disciplines.
This course may not be repeated for credit.
Prerequisite(s)
- Software Engineering for Engineers 300; and 3 units from Engineering 319, Digital Engineering 319 or Electrical Engineering 419; and 3 units from Software Engineering for Engineers 337, Computer Engineering 335, 339, or Geomatics Engineering 333.
Antirequisite(s)
- Credit for Software Engineering for Engineers 444 and Software Engineering for Engineers 544 will not be allowed.
Sections
This course will be offered next in
Winter 2025.