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 461 or Stat 410 and one of CS 101 or 125 or equivalent.
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: All exams in this course may be taken online. Please see our Proctor Information for further instructions.
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.
Your time in the course begins on the date your registration is processed. This course is 16 weeks long with the possibility of purchasing an extension.