Description
Dr. Sreedath Panat introduces mathematical ideas used to reason about machine-learning models. The linear-algebra material examines inner products and linear transformations, then uses eigenvalues and eigenvectors to describe how transformations affect directions and scaling.
Calculus topics include definite and indefinite integrals and the relationship between integration and differentiation. The course combines theory with exercises and project-oriented examples so that learners can connect the notation with the mathematical foundations needed for further AI and machine-learning study.
Intended audience: Students and professionals strengthening the mathematical basis for machine-learning study. Participants in Vizuara's AI and generative-AI learning paths.
What you will learn
- Interpret inner products and linear transformations.
- Use eigenvalues and eigenvectors to reason about transformations.
- Distinguish definite and indefinite integration.
- Explain the relationship between derivatives and integrals.
Course specifications
- Publisher
- vizuara
- Instructors
- Dr. Sreedath Panat
- Lecture count
- 24
- Quality
- 1080p
- Level
- Beginner to Advanced
- Duration
- 27 hours and 45 minutes
- Subtitle
- None
- Edition
- 2026-8
Course topics
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Pictures
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Introduction video
How to open the files
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2026-8 · 1080p · 1
Direct downloads
2026-8 · 1080p
2026-8 · 1080p · 2
Rapidgator
2026-8 · 1080p
Size
5.7 GB
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