
Linear Algebra Course – Mathematics for Machine Learning and Generative AI
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This independent-study version of MIT's linear algebra course is built around Professor Gilbert Strang's lectures. The package pairs each video with summary notes and suggested readings from his textbook. Problem-solving videos from an MIT recitation instructor, problem sets with solutions, and full exams add practice across the topics.
The course is aimed at people in physics, economics, the social and natural sciences, and engineering, where matrix methods are used as working tools. Its balance of theory and applications suits learners who want to understand the mechanics behind linear systems and then test that understanding on their own.
This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering. It parallels the combination of theory and applications in Professor Strang’s textbook {{% resource_link "4cdcc772-348a-4e48-9678-0a6cc9328fde" "_Introduction to Linear Algebra_" %}}.
Course Format
This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:
- A complete set of **Lecture Videos** by Professor Gilbert Strang.
- **Summary Notes** for all videos along with suggested readings in Prof. Strang's textbook {{% resource_link "4cdcc772-348a-4e48-9678-0a6cc9328fde" "_Linear Algebra_" %}}.
- **Problem Solving Videos** on every topic taught by an experienced MIT Recitation Instructor.
- **Problem Sets** to do on your own with **Solutions** to check your answers against when you're done.
- A selection of **Java® Demonstrations** to illustrate key concepts.
- A full set of **Exams with Solutions**, including review material to help you prepare.
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