Suggested preparation: Linear algebra, programming and basic statistics.
Optional preparation: Integrated Mathematics 1: Free Course.
About this course
Study mathematical representations used in large-scale data analysis. The collection connects associative arrays, machine learning and worked computational examples, including sequence comparison.
Topics and lesson examples
- 1. Artificial Intelligence and Machine Learning
- 1. Using Associative Arrays
- 3. Examples Demonstration
- 5. Examples Demonstration
- 7. Examples Demonstration
Course at a glance
| Provider | MIT |
|---|---|
| Platform | YouTube · MIT OpenCourseWare |
| Access | Free Video |
| Level | Professional — WikiFree study-level assessment |
| Language | English |
| Available lessons | 20 |
| Video duration | 14h 12m · self-paced |
| Details checked | 10 October 2026 |
Preparation and study approach
Suggested preparation: Linear algebra, programming and basic statistics.
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 optionIntegrated Mathematics 1: Free Course
Focus: Linear modeling · Functions and sequences
Intermediate - Review a lower-level optionGet Ready for Grade 8 Mathematics: Free Course
Focus: Mathematical reasoning · Worked solutions
Beginner - Review a lower-level optionIntegrated Mathematics 2: Free Course
Focus: Quadratic functions · Polynomial structure
Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free MIT Course: Mathematics for Big Data and Machine Learning | Professional | 1. Artificial Intelligence and Machine Learning · 1. Using Associative Arrays · 3. Examples Demonstration | 14h 12m of video; practice time is additional |
| Integrated Mathematics 1: Free Course | Intermediate | Linear modeling · Functions and sequences · Coordinate geometry | 25h 46m of video; practice time is additional |
| Get Ready for Grade 8 Mathematics: Free Course | Beginner | Mathematical reasoning · Worked solutions · Notation | 4h 54m of video; practice time is additional |
| Integrated Mathematics 2: Free Course | Intermediate | Quadratic functions · Polynomial structure · Geometry | 26h 20m of video; practice time is additional |
Provider: MIT. Videos play from the MIT OpenCourseWare channel on YouTube.
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