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Rigorous Applied Data Science Program leveraging AI for effective decision making. Become a data-driven decision maker with live virtual teaching from MIT faculty.
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This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems.
Jun 24, 2024 · MIT OpenCourseWare is an online publication of materials from over 2,500 MIT courses, freely sharing knowledge with learners and educators around the world. Learn more
- Assignments | Signals and Systems | Supplemental Resources | MIT OpenCourseWare
- Unit I: Ax = b and the Four Subspaces | Linear Algebra | Mathematics | MIT OpenCourseWare
- Lecture Notes | Introduction to C++ | Electrical Engineering and Computer Science | MIT OpenCourseWare
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Topics. This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction. It includes formulation of learning problems and concepts of representation, over-fitting, and generalization.
Master the calculus of derivatives, integrals, coordinate systems, and infinite series. In this three-part series you will learn the mathematical notation, physical meaning, and geometric interpretation of a variety of calculus concepts.
This is MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow.
This course is the first half of the year-long introductory graduate sequence 18.745/18.755 on Lie groups and Lie algebras. Topics include foundations of the theory of Lie groups and Lie algebras; theorems of Engel and Lie; the universal enveloping algebra, the Poincare-Birkhoff-Witt theorem; free Lie algebras; the Campbell-Hausdorff formula; classification and structure of finite dimensional ...
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Topics include regular and context-free languages, decidable and undecidable problems, reducibility, recursive function theory, time and space measures on computation, completeness, hierarchy theorems, inherently complex problems, oracles, probabilistic computation, and interactive proof systems.
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Learn to Challenge Common Misconceptions Surrounding AI in this Online Course From MIT. Learn to Embrace AI as Part of a Transformative Toolkit in this 6-Week Online Course.
professional-education-gl.mit.edu has been visited by 10K+ users in the past month
Rigorous Applied Data Science Program leveraging AI for effective decision making. Become a data-driven decision maker with live virtual teaching from MIT faculty.