MIT 6.006 Introduction to Algorithms: study plan and how long it takes
The MIT OpenCourseWare playlist is 32 videos and 35.3 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.
32 videos · 35.3 hours · MIT OpenCourseWare
MIT 6.006 is MIT's core undergraduate algorithms course. The Spring 2020 version, released on MIT OpenCourseWare, covers data structures, sorting, graph algorithms and dynamic programming, with lecture notes, problem sets and quizzes available on the OCW site.
The playlist mixes 21 lectures (about 19.4 hours) with problem sessions and quiz reviews. The structure follows the real course: three blocks, each ending in a quiz, which makes a natural study plan.
Who it's for: Students and self-learners who know basic programming (the course uses Python) and some discrete maths, and want a rigorous university-level algorithms course.
How long does it take?
The full playlist is 35.3 hours across 32 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 | 71 days | 48 days | 36 days |
| 1 h a day | 36 days | 24 days | 18 days |
| 2 h a day | 18 days | 12 days | 9 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 1–7 · 7h 8m
Day 1 · 46m
- 11. Algorithms and Computation46m
Day 2 · 50m
- 22. Data Structures and Dynamic Arrays50m
Day 3 · 1h 27m
- 3Introduction to Algorithms - Problem Session 1: Asymptotic Behavior of Functions and Double-ended...1h 27m
Day 4 · 53m
- 43. Sets and Sorting53m
Day 5 · 53m
- 54. Hashing53m
Day 6 · 1h 28m
- 6Problem Session 2 (MIT 6.006 Introduction to Algorithms, Spring 2020)1h 28m
Day 7 · 52m
- 75. Linear Sorting52m
Week 2Videos 8–14 · 7h 51m
Day 8 · 1h 26m
- 8Problem Session 31h 26m
Day 9 · 51m
- 96. Binary Trees, Part 151m
Day 10 · 54m
- 107. Binary Trees, Part 2: AVL54m
Day 11 · 1h 30m
- 11Problem Session 41h 30m
Day 12 · 51m
- 128. Binary Heaps51m
Day 13 · 53m
- 139. Breadth-First Search53m
Day 14 · 1h 26m
- 14Quiz 1 review1h 26m
Week 3Videos 15–21 · 7h 37m
Day 15 · 52m
- 1510. Depth-First Search52m
Day 16 · 58m
- 1611. Weighted Shortest Paths58m
Day 17 · 1h 28m
- 17Problem Session 51h 28m
Day 18 · 58m
- 1812. Bellman-Ford58m
Day 19 · 57m
- 1913. Dijkstra57m
Day 20 · 1h 26m
- 20Problem Session 71h 26m
Day 21 · 57m
- 2114. APSP and Johnson57m
Week 4Videos 22–28 · 8h
Day 22 · 1h 23m
- 22Quiz 2 Review1h 23m
Day 23 · 57m
- 2315. Dynamic Programming, Part 1: SRTBOT, Fib, DAGs, Bowling57m
Day 24 · 59m
- 2416. Dynamic Programming, Part 2: LCS, LIS, Coins59m
Day 25 · 1h 35m
- 25Problem Session 81h 35m
Day 26 · 1h 4m
- 2617. Dynamic Programming, Part 3: APSP, Parens, Piano1h 4m
Day 27 · 1h 4m
- 2718. Dynamic Programming, Part 4: Rods, Subset Sum, Pseudopolynomial1h 4m
Day 28 · 59m
- 2819. Complexity59m
Week 5Videos 29–32 · 4h 45m
Day 29 · 1h 25m
- 29Problem Session 91h 25m
Day 30 · 1h 24m
- 30Quiz 3 Review1h 24m
Day 31 · 56m
- 3120. Course Review56m
Day 32 · 59m
- 3221. Algorithms—Next Steps59m
Study plan, phase by phase
Video numbers are positions in the playlist. To schedule just one phase, enter its numbers in the planner's From and To fields.
- 01
Block 1: data structures and sorting
Videos 1–14 · 14h 59m
Algorithms and computation, dynamic arrays, sets and sorting, hashing, linear sorting, binary trees and AVL trees, binary heaps and BFS, with problem sessions 1 to 4 and the Quiz 1 review.
- 02
Block 2: graph algorithms
Videos 15–22 · 8h 59m
Depth-first search, weighted shortest paths, Bellman-Ford, Dijkstra, all-pairs shortest paths and Johnson's algorithm, with problem sessions and the Quiz 2 review.
- 03
Block 3: dynamic programming and complexity
Videos 23–30 · 9h 27m
Four dynamic programming lectures built around the SRTBOT framework, then complexity, with problem sessions and the Quiz 3 review.
- 04
Course review and next steps
Videos 31–32 · 1h 55m
A full course review and a final lecture on where to go next in algorithms.
Tips for finishing
- Short on time? The 21 numbered lectures are 19.4 hours on their own. Tick off the problem sessions and quiz reviews in the playlist length calculator and the planner will schedule lectures only.
- Do the problem sets from the OCW site between blocks. The problem sessions make much more sense after you've tried them.
- Watch lectures at 1.25x; the pace is deliberate and the board work is easy to follow.