Suggested preparation: Algorithms, data structures, discrete mathematics and proofs.
Optional preparation: Free MIT Course: Algorithms and Data Structures.
About this course
Extend your algorithmic toolkit through amortized analysis, augmented structures, matching and parameterized complexity. MIT lectures focus on design techniques and arguments about efficiency.
Topics and lesson examples
- 1. Course Overview, Interval Scheduling
- R4. Randomized Select and Randomized Quicksort
- R6. Greedy Algorithms
- 18. Complexity: Fixed-Parameter Algorithms
- 24. Cache-Oblivious Algorithms: Searching & Sorting
Course at a glance
| Provider | MIT |
|---|---|
| Platform | YouTube · MIT OpenCourseWare |
| Access | Free Video |
| Level | Professional — WikiFree study-level assessment |
| Language | English |
| Available lessons | 34 |
| Video duration | 39h 28m · self-paced |
| Details checked | 10 October 2026 |
Preparation and study approach
Suggested preparation: Algorithms, data structures, discrete mathematics and proofs.
Follow the available videos in sequence, pausing to summarize the main argument or reconstruct a worked example. Keep a short list of assumptions, unfamiliar terms and questions to revisit. Additional reading, problem solving and practice will take time beyond the listed video duration.
Using this video classroom
Select a lesson from the list, or search for a topic. Previous and Next move through the sequence. You can mark lessons complete; progress is stored in this browser without a WikiFree account.
Free access and course scope
The public MIT OpenCourseWare videos in this classroom are free to watch. This listing provides the available playlist recordings, which may include selected lectures, recitations, demonstrations or supporting discussions rather than every component of the original campus course. Textbooks, equipment, software licenses, supervised labs, graded assignments and instructor feedback are not supplied by WikiFree. No purchase is required to watch the videos or use the note-based study approach above.
WikiFree independently organizes these resources for self-paced study. Watching does not award an MIT certificate, academic credit or admission to MIT.
Video provider and credit: MIT OpenCourseWare on YouTube. WikiFree titles, descriptions and cover artwork are independently prepared.
Related courses for your next step
- Review a lower-level optionFree MIT Course: Algorithms and Data Structures
Focus: 1. Algorithms and Computation · Problem Session 3
Intermediate - Review a lower-level optionFree Simplilearn Course: Data Structures and Algorithms
Focus: Arrays & Lists · Trees & Graphs
Intermediate - Compare another approachFree MIT Course: Computational Complexity and Algorithmic Lower Bounds
Focus: 1. Overview · 6. Circuit SAT
Professional
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free MIT Course: Algorithm Design and Complexity Analysis | Professional | 1. Course Overview, Interval Scheduling · R4. Randomized Select and Randomized Quicksort · R6. Greedy Algorithms | 39h 28m of video; practice time is additional |
| Free MIT Course: Algorithms and Data Structures | Intermediate | 1. Algorithms and Computation · Problem Session 3 · 11. Weighted Shortest Paths | 35h 19m of video; practice time is additional |
| Free Simplilearn Course: Data Structures and Algorithms | Intermediate | Arrays & Lists · Trees & Graphs · Search & Sort | 56h 43m of video; practice time is additional |
| Free MIT Course: Computational Complexity and Algorithmic Lower Bounds | Professional | 1. Overview · 6. Circuit SAT · 12. Gaps and PCP | 31h 3m of video; practice time is additional |
Provider: MIT. Videos play from the MIT OpenCourseWare channel on YouTube.
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