Course Syllabus

Our Public Course Page is the primary source for course info and materials.

There you will find the syllabus, FAQ, preparation guide, and other resources.

Course Helpline:

Prerequisites: In order to get the most out of CS109A, knowledge of multivariate calculus, probability theory, statistics, and some basic linear algebra (e.g., matrix operations, eigenvectors, etc.) is suggested but not required.  Below are some resources for self-assessment and review:

Multivariate Calculus: multiple exams w/ solutions
Linear Algebra: multiple exams /w solutions [1], [2]
Probability: exams w/ solutions & problem sets w/ solutions
Statistics: multiple pairs of exam questions and answers [Q1], [A1], [Q2], [A2], [Q3], [A3]

Here is a useful textbook for reviewing many of the above topics: Mathematics for Machine Learning

Note: you can be successful in the course (assignments, quizzes, etc.) with the listed pre-requisites, but some of the material presented in lecture may be more easily understood with more background.


Harvard Extension School Policies:

The Extension School is committed to providing an accessible academic community. The Accessibility Office offers a variety of accommodations and services to students with documented disabilities. Please visit for more information.

You are responsible for understanding Harvard Extension School policies on academic integrity ( and how to use sources responsibly. Not knowing the rules, misunderstanding the rules, running out of time, submitting the wrong draft, or being overwhelmed with multiple demands are not acceptable excuses. There are no excuses for failure to uphold academic integrity. To support your learning about academic citation rules, please visit the Harvard Extension School Tips to Avoid Plagiarism (, where you'll find links to the Harvard Guide to Using Sources and two free online 15-minute tutorials to test your knowledge of academic citation policy. The tutorials are anonymous open-learning tools.

Course Summary:

Date Details Due