MIT 6.0001 Introduction to Computer Science and Programming in Python: study plan and how long it takes
The MIT OpenCourseWare playlist is 38 videos and 10.0 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.
38 videos · 10.0 hours · MIT OpenCourseWare
MIT 6.0001 (Fall 2016), taught by Ana Bell, is MIT's introduction to computer science using Python: computation, branching and iteration, string manipulation and approximation methods, decomposition and functions, tuples and lists, recursion and dictionaries, testing and exceptions, object-oriented programming and program efficiency.
The playlist interleaves the 12 full lectures with short clips of individual concepts from them.
Who it's for: Beginners who want a university-level first course in programming, with problem sets from MIT OpenCourseWare.
How long does it take?
The full playlist is 10.0 hours across 38 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 | 20 days | 14 days | 10 days |
| 1 h a day | 10 days | 7 days | 5 days |
| 2 h a day | 5 days | 4 days | 3 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 2 weeks in total. For a different pace, start date or speed, use the planner above.
Week 1Videos 1–26 · 5h 47m
Day 1 · 48m
- 11. What is Computation?43m
- 2Shell vs. Editor1m
- 3Python vs. Math2m
- 4Bindings2m
Day 2 · 51m
- 52. Branching and Iteration44m
- 6Strings1m
- 7Comparisons1m
- 8Branching1m
- 9While Loops2m
- 10For Loops2m
Day 3 · 52m
- 113. String Manipulation, Guess and Check, Approximations, Bisection45m
- 12String Manipulations3m
- 13For Loops With Strings4m
Day 4 · 47m
- 144. Decomposition, Abstraction, and Functions41m
- 15Function Calls3m
- 16Functions as Arguments4m
Day 5 · 53m
- 175. Tuples, Lists, Aliasing, Mutability, and Cloning41m
- 18Tuples3m
- 19Simple Lists3m
- 20List Operations3m
- 21List Aliasing/Mutation2m
Day 6 · 48m
- 226. Recursion and Dictionaries48m
Day 7 · 48m
- 237. Testing, Debugging, Exceptions, and Assertions42m
- 24Black Box and Glass Box Testing2m
- 25Errors1m
- 26Exceptions3m
Week 2Videos 27–38 · 4h 12m
Day 8 · 50m
- 278. Object Oriented Programming42m
- 28Class Definition1m
- 29Class Instance2m
- 30Methods1m
- 31Method Call2m
- 32Special Methods2m
Day 9 · 52m
- 339. Python Classes and Inheritance47m
- 34Getters and Setters2m
- 35Subclass3m
Day 10 · 51m
- 3610. Understanding Program Efficiency, Part 151m
Day 11 · 49m
- 3711. Understanding Program Efficiency, Part 249m
Day 12 · 49m
- 3812. Searching and Sorting49m
Tips for finishing
- The short clips repeat parts of the lectures. If you watch the full lectures, tick the clips off in the playlist length calculator and the planner will skip them.
- Follow it with MIT 6.0002, which continues into computational thinking and data science.