Math 490: Mathematics of Machine Learning


Machine learning is a growing field at the intersection of probability, statistics, optimization, and computer science, which aims to develop algorithms for making predictions based on data. This course will cover foundational models and mathematics for machine learning, including statistical learning theory and neural networks with a project component.


Math 490 Syllabus


Math 461 or Stat 410 and one of CS 101 or 125 or equivalent.

Credit Hours


Undergraduate Students  
Graduate Students  
Courseware Cost None

Students must be able to print out assignments, write out solutions, then scan their written work and upload them to Moodle.

Students will use Python both within the lessons and to complete two midterm projects and will need to download and use Anaconda software to their computer.


Exams: This course requires two paper-based midterm exams. Students will schedule their exams with NetMath and access their exams online. There is also a Python-based final project.

Proctorship Information: Exams in this course may be taken online.

Students with a course start date prior to January 1st, 2023 should use proctor information on this page to take their exams.

Students with a course start date on or after January 1st, 2023 should refer to this page for exam taking information.

Once registered, students will find relevant exam taking information and all other course requirements within their Nexus student dashboard.


Course Options

Please Note:

Students currently registered in a University of Illinois Graduate Degree program will be restricted from registering in 16-week Academic Year-term NetMath courses. Matriculating UIUC Grad students will be allowed to register in Summer Session II NetMath courses. 

This page has information regarding the self-paced, rolling enrollment course. If you are a UIUC student interested in taking a course during the summer, you may be interested in a Summer Session II course.


Individual students enrolled in this course are assigned to a course instructor. 

Course Timeline

Time in the course begins on the date your registration is processed. This course is 16 weeks long with the possibility of purchasing up to two 1-month extensions.

Students with course start dates prior to 1/1/2023:

Click here for information about extensions for this course. Click here to apply for an extension.

Students with course start dates on or after 1/1/2023:

Extension information is posted here. Extension applications must be made via the student Nexus Dashboard. Nexus access will be granted upon course registration.