CP322F - Machine Learning (Winter 2027)

Position Summary

With the rise of Data Science and Big Data, machine learning has been recognized as the key driver behind successful advances of these fields. However, many recent entrants to the field can only utilize the variety of machine learning algorithms as black boxes. This aims to empower to effectively use and understand the primary topics in predictive models, including regressions, classifications, neural networks and deep learning, ensemble-based methods, performance evaluation, etc. In addition, the course provides case studies that describe specific data analytics projects, and provide opportunities to employ a variety of machine learning toolboxes

Qualifications – Required: Master’s degree
Qualifications - Areas of Specialization: n/a
Qualifications – Discipline: Computer Science or related field
Qualifications - Professional Designation: PhD would be an asset
Qualifications – Other: