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COMP 3948 Predictive Modelling

Undergraduate Studies
Professor / Instructor
Pat McGee
Sep. 8, 2021-Dec. 10, 2021

This code intensive course introduces modeling techniques for predicting binary, probability, ordinal and categorical outcomes. Modeling includes popular forms of regression and clustering. Introductory math and statistics behind the fundamental models are discussed and practiced. Use cases and exercises examine eliminating bias at each step of the modeling process. Common sampling methods for training and testing are used to assist with model validation. Techniques for treating missing values, transforming outliers, manufacturing variables and selecting variables are covered. Dimension reduction through principal component analysis is introduced. Analysis of variance is studied and also enhanced with factor analysis. Course work iterates over exploratory analysis and model reporting phases with statistical summaries and visual analytics for reinforcement of learning.
Prerequisite(s): Completion of first year CST and admission into the Predictive Analytics Option.

You are applying for a $500 scholarship towards a qualifying course at one of our post-secondary education partners: BCIT, Northeastern University, SFU or UBC. Applicants must be either Canadian Citizens, BC permanent residents or working towards obtaining one of these.

Please only apply for this scholarship once you have been enrolled or waitlisted in an applicable course. We will be confirming all student details with instructors.

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