Machine Learning Concepts and Usage
University of Manitoba · MB · COMP3360
Machine Learning Concepts and Usage is a subject at University of Manitoba, MB. It covers topics like data-mining, deep-learning, knowledge-discovery, machine-learning. It is part of 3 degrees. The information below is compiled from public course material — approximate, not official.
University of Manitoba
COMP3360
3.00
Topics covered
Degrees that include Machine Learning Concepts and Usage
Frequently asked questions
What is Machine Learning Concepts and Usage about?
Machine Learning Concepts and Usage covers topics like data-mining, deep-learning, knowledge-discovery, machine-learning.
Which degrees include Machine Learning Concepts and Usage?
Machine Learning Concepts and Usage is part of 3 degrees, including Computer Science, B.Sc. Major, Data Science, B.Sc. Major, Statistics, B.Sc. Major.
How many credit points is Machine Learning Concepts and Usage?
Machine Learning Concepts and Usage at University of Manitoba is typically around 3.00 credit points. Approximate — confirm with the university.
Where is Machine Learning Concepts and Usage taught?
Machine Learning Concepts and Usage is taught at University of Manitoba, MB.
Studying Machine Learning Concepts and Usage?
Peernovo helps students research, choose and thrive at university — across Australia, the US, the UK and Canada — powered by our AI backbone:
- Explore & compare degrees — across universities and countries with honest, specific information.
- "What Can I Be?" career guidance — an AI pathway councillor that maps degrees to careers.
- See who's studying — your degree at your university — find classmates and study groups.
- AI Task Coach — a Socratic study companion that plans your work around your life.
- Honours & Thesis Research Coach — structure and move your research project forward.
- Smart study planner, exam prep and a daily digest — to keep you on track.
Sources: University of Manitoba public course catalogue. Information is compiled and summarised — not copied verbatim — and is approximate; always confirm with the original source.
Something not right on this page, or want it changed? Let us know and we'll review it.