Introduction to Machine Learning
Spring 2026
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 §
We will be meeting for Lectures on Mondays, Labs on Wednesdays, and Recitations on Thursdays/Fridays.
3.1) Lectures §
Monday lectures anchor the week's discussion, cover the technical contents, and tie together the high-level motivations, concepts, and stories. Lectures are held class-wide Mondays 3-4:30pm, in 10-250. Recordings are available shortly after live sessions.
Our first class meeting will be the lecture on Monday, Feb 2, 2026.
3.2) Labs §
Wednesday labs engage students with each other in small teams and with staff to explore fundamental concepts. Labs are held in small sections:
| Section | Time | Room | |
|---|---|---|---|
| 1 | Wednesday, 9:30am-11am | 34-501 | |
| 2 | Wednesday, 11am-12:30pm | 34-501 | |
| 3 | Wednesday, 11am-12:30pm | 32-044 | |
| 4 | Wednesday, 1pm-2:30pm | 34-501 | |
| 5 | Wednesday, 1pm-2:30pm | 32-044 | |
| 6 | Wednesday, 2:30pm-4pm | 34-501 |
Each student will be assigned a lab section and is expected to attend only their assigned section. A self-switching mechanism will be made available starting Feb 2, 2026, at 5 PM.
3.3) Recitations §
Thursday/Friday recitations cover examples and pen-paper problems to reinforce problem-solving skills. Recitations are held in small sections:
| Section | Time | Room | |
|---|---|---|---|
| R1 | Thursday, 11am-12:30pm | 45-102 | |
| R2 | Thursday, 1pm-2:30pm | 32-044 | |
| R3 | Thursday, 2:30pm-4pm | 32-044 | |
| R4 | Friday, 11am-12:30pm | 45-102 |
You're welcome to attend any recitation section that fits your schedule, subject to room capacity.
4) Cross-registration §
We appreciate your interest in the course. Our space is limited, and cross-registration requests are considered on a rolling basis as enrollment becomes stable.
If space becomes available, we will post further updates — including a sign-up form, if applicable — on January 16, 2026, at 5pm (Friday, after MIT Spring pre-registration ends) on the IntroML homepage here.
There's no need to email us separately — if space opens up, the form will be the only step needed.
Thank you for your interest and understanding.
5) Listeners §
Due to capacity and other constraints, we will not be able to accept Listener registrants. That said, most of the course materials are openly accessible.6) LA Applications §
LA Applications for 6.390 will open at the LA application site in late December/early January. Please stay tuned. Announcements about the LA applications will be made via 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!