CMPUT 267: Machine Learning I

Course description

This course introduces the fundamental statistical, mathematical, and computational concepts in analyzing data. The goal for this introductory course is to provide a solid foundation in the mathematics of machine learning, in preparation for more advanced machine learning concepts. The course focuses on univariate models, to simplify some of the mathematics and emphasize some of the underlying concepts in machine learning, including how should one think about data; how can data be summarized; how models can be estimated from data; what sound estimation principles look like; how generalization is achieved; and how to evaluate the performance of learned models.

Lectures

Lectures are scheduled for Tuesdays and Thursdays, 12:30–1:50 p.m., in CCIS 1-440. Lectures will normally be held in person; one or two lectures may be delivered remotely, with details announced in advance. Lectures will not be recorded.

Office hours

Office hours will be held through a mix of in-person and Zoom sessions, at the discretion of the course staff. Times and access information will be posted later.

Course work

Grading structure

• Assignments: 10%
• In-class quizzes: 30%
• Midterm: 30%
• Final exam: 30%

Assignments

Assignments will be graded on a completion basis. Details and due dates will be posted during the term. No late assignments will be accepted unless there are protected medical or non-medical reasons.

In-class quizzes

There will be approximately 10 in-class quizzes, all taken during class. There are no make-up quizzes. Your lowest three quiz scores will be dropped.

Midterm

Midterm details will be announced during the term.

Final exam

Final-exam details will be announced during the term.

AI policy

You may use AI tools to help understand course concepts. Further assessment-specific guidance will be provided with each assignment or assessment.

Communication and support

Please use Piazza for all course communication; I will not be reachable by email for course questions. You may post private questions on Piazza. Office hours will be announced before the term begins.