MIT 18.06 Linear Algebra (Gilbert Strang): study plan and how long it takes
The MIT OpenCourseWare playlist is 36 videos and 28.0 hours long. Here's how long it takes at different paces, a week-by-week schedule built from the real videos, and a planner that turns it into your own daily plan.
36 videos · 28.0 hours · MIT OpenCourseWare
Gilbert Strang's MIT 18.06 (Spring 2005) is perhaps the most famous maths course online. It covers solving linear systems, elimination and matrix multiplication, inverses, vector spaces, column space and nullspace, independence and basis, orthogonality and projections, least squares, determinants, eigenvalues and eigenvectors, positive definite matrices and the SVD.
Strang's teaching makes the four fundamental subspaces genuinely clear, and the course materials are on MIT OpenCourseWare.
Who it's for: Students and engineers, especially those heading into machine learning, who want a deep, classic linear algebra course.
How long does it take?
The full playlist is 28.0 hours across 36 videos. Here's roughly how many days that is at different daily watch times and speeds, counting video time only:
| Daily time | At 1x | At 1.5x | At 2x |
|---|---|---|---|
| 30 min a day | 56 days | 38 days | 28 days |
| 1 h a day | 28 days | 19 days | 14 days |
| 2 h a day | 14 days | 10 days | 7 days |
Make your own schedule
The playlist link is already filled in. Press Plan, set how much time you have each day and your speed, and you'll get a day-by-day schedule with a finish date and a calendar file. It reads the live playlist, so new videos are included.
Week-by-week schedule
A sample plan at 1 hour a day and normal speed, using whole videos so none is split across days. That's 5 weeks in total. For a different pace, start date or speed, use the planner above.
Week 1Videos 1–8 · 5h 27m
Day 1 · 47m
- 1An Interview with Gilbert Strang on Teaching Linear Algebra8m
- 21. The Geometry of Linear Equations40m
Day 2 · 48m
- 32. Elimination with Matrices.48m
Day 3 · 47m
- 43. Multiplication and Inverse Matrices47m
Day 4 · 48m
- 54. Factorization into A = LU48m
Day 5 · 48m
- 65. Transposes, Permutations, Spaces R^n48m
Day 6 · 46m
- 76. Column Space and Nullspace46m
Day 7 · 43m
- 87. Solving Ax = 0: Pivot Variables, Special Solutions43m
Week 2Videos 9–15 · 5h 38m
Day 8 · 47m
- 98. Solving Ax = b: Row Reduced Form R47m
Day 9 · 50m
- 109. Independence, Basis, and Dimension50m
Day 10 · 49m
- 1110. The Four Fundamental Subspaces49m
Day 11 · 46m
- 1211. Matrix Spaces; Rank 1; Small World Graphs46m
Day 12 · 48m
- 1312. Graphs, Networks, Incidence Matrices48m
Day 13 · 48m
- 1413. Quiz 1 Review48m
Day 14 · 50m
- 1514. Orthogonal Vectors and Subspaces50m
Week 3Videos 16–22 · 5h 51m
Day 15 · 49m
- 1615. Projections onto Subspaces49m
Day 16 · 48m
- 1716. Projection Matrices and Least Squares48m
Day 17 · 49m
- 1817. Orthogonal Matrices and Gram-Schmidt49m
Day 18 · 49m
- 1918. Properties of Determinants49m
Day 19 · 53m
- 2019. Determinant Formulas and Cofactors53m
Day 20 · 51m
- 2120. Cramer's Rule, Inverse Matrix, and Volume51m
Day 21 · 51m
- 2221. Eigenvalues and Eigenvectors51m
Week 4Videos 23–29 · 5h 45m
Day 22 · 52m
- 2322. Diagonalization and Powers of A52m
Day 23 · 51m
- 2423. Differential Equations and exp(At)51m
Day 24 · 51m
- 2524. Markov Matrices; Fourier Series51m
Day 25 · 48m
- 2624b. Quiz 2 Review48m
Day 26 · 44m
- 2725. Symmetric Matrices and Positive Definiteness44m
Day 27 · 48m
- 2826. Complex Matrices; Fast Fourier Transform48m
Day 28 · 51m
- 2927. Positive Definite Matrices and Minima51m
Week 5Videos 30–36 · 5h 19m
Day 29 · 46m
- 3028. Similar Matrices and Jordan Form46m
Day 30 · 40m
- 3129. Singular Value Decomposition40m
Day 31 · 49m
- 3230. Linear Transformations and Their Matrices49m
Day 32 · 50m
- 3331. Change of Basis; Image Compression50m
Day 33 · 47m
- 3432. Quiz 3 Review47m
Day 34 · 42m
- 3533. Left and Right Inverses; Pseudoinverse42m
Day 35 · 43m
- 3634. Final Course Review43m
Tips for finishing
- Plan three lectures a week alongside his textbook or the OCW problem sets.
- Watch 3Blue1Brown's Essence of Linear Algebra first or alongside for the geometric intuition.