Introduction to Machine Learning
(Fall 2025)
Pre-semester Information
👋 Hi there! Welcome to 6.390!
1) Course Overview §
6.390 introduces the principles and algorithms of machine learning from an optimization perspective. Topics include linear and non-linear models for supervised, unsupervised, and reinforcement learning, with a focus on gradient-based methods and neural-network architectures. Enrollment may be limited.2) Prerequisites §
Concretely, things we expect you to know (we use these constantly, but don't teach them explicitly):2.1) Programming §
- Intermediate Python, including the notion of classes.
- Exposure to algorithms – ability to understand & discuss pseudo-code, and implement in Python.
2.2) Linear Algebra §
- Fundamental matrix concepts and manipulations, e.g., rank, multiplication, and inverse.
- Points and planes in high-dimensional space.
- Basic matrix calculus, e.g., gradients.
6.1010 or 6.1210 can serve as the programming prerequisite. 18.06, 18.C06, 18.03, or 18.700 can serve as the linear algebra prerequisite.
(For each of these courses above, a link points to a representative syllabus from some past semesters, for reference.)
3) Class Meeting and Sections §
Our class meetings will be on Thursdays for lectures, Fridays for recitations, and Tuesdays for labs.3.1) Lectures §
Lectures anchor the week's discussion, overview the technical content, and tie together the high-level motivations, concepts, and stories. They are held class-wide on Thursdays, 11–12:30pm in 10-250. Recordings are available shortly afterward.3.2) Recitations §
Recitations reinforce problem-solving skills through examples and pen-and-paper problems. Recitations are held in four sections, all in 32-044: 10-11am, 11am-12pm, 1-2pm, and 2-3pm.
You're welcome to attend any recitation section that fits your schedule, subject to room capacity.
3.3) Labs §
Labs engage students in team-based, hands-on exploration of core concepts, guided by staff. Labs are held in six sections:| Section | Time | Room | |
|---|---|---|---|
| 1 | Tuesday, 9am-11am | 34-501 | |
| 2 | Tuesday, 11am-1pm | 34-501 | |
| 3 | Tuesday, 11am-1pm | 32-044 | |
| 4 | Tuesday, 1pm-3pm | 34-501 | |
| 5 | Tuesday, 1pm-3pm | 32-044 | |
| 6 | Tuesday, 3pm-5pm | 34-501 |
You will be assigned a lab section and are expected to attend only your assigned section. A mechanism for self-switching sections will be made available.
4) Cross-registration §
We appreciate your interest! Due to space constraints, cross-registration requests will be considered after enrollment stabilizes. We will post updates here about whether and how cross-registration can be accommodated on:
- August 22 (after MIT Fall pre-registration ends), and
- September 6 (after MIT Fall registration ends).
5) Listeners §
Due to capacity constraints, we will not be able to accommodate listeners. However, course notes and lecture slides will be publicly available.6) LA Applications §
LA Applications for 6.390 will open at the LA application site in late July/early August. Please stay tuned. Announcements about the LA applications will be made via the 6.AcAd forum and EECS jobs list.
Alums, we invite you to join our team!
7) Course Number Change§
Since Fall 2022, all MIT EECS (Course 6) subjects have been renumbered (rationale and details can be found here). This subject used to be called 6.036; moving forward, we'll refer to it internally as 6.390 ("six three-nine-oh"). But for registration purposes, please register for 6.3900 (note the extra zero).
8) Other Questions?§
Feel free to drop us an email at
6.390-inquiry@mit.edu. We'd love to
hear from you!