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EXSC2500 Python Programming and Machine Learning 1 Course Page

Description: Learn Python programming as part of an introduction to machine learning (ML) applications. No previous programming experience is required, but learners must have basic computer and high-school algebra skills. The main topics are: variables, expressions, conditional execution, iteration, functions, how to edit/execute/debug python programs, testing, parsing, computational problem solving, and iterative software development. Includes hands-on, in-class exercises, students must be prepared to (in class) write Python programs, individually or in a group.

EXSC2501 Python Programming and Machine Learning 2 Course Page

Description: Learn intermediate Python programming and how to program a machine learning (ML) application. The class will implement a binary Naive Bayes classifier from scratch, over the course. Important ML concepts such as supervised learning, quality training data, cross validation, precision, recall, and a confusion matrix will be discussed and implemented in Python. Includes hands-on, in-class exercises, students must be prepared to (in class) write Python programs, individually or in a group. Prerequisite: EXSC 2500