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1. ocw.mit.eduMIT OpenCourseWare | Free Online Course Materials

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   17 de jul. de 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

2. web.mit.edu › coursesEducation | MIT - Massachusetts Institute of Technology

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   From science and engineering to the arts, humanities, social sciences, and interdisciplinary programs, we offer excellence across the board. Our undergraduates work closely with faculty, tackle global challenges , pursue fundamental questions, and translate ideas into action.

3. openlearning.mit.eduMIT Open Learning brings Online Learning to MIT and the world

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   View online courses corresponding to the STEM classes taken by first-year students at MIT.

4. openlearning.mit.edu › courses-programsOnline, Blended, Professional & Free Courses from MIT

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   Upskill, and continue your learning journey with MIT through online, blended and free and open courses. Earn a professional certificate or learn a new skill with MIT today!

5. openlearning.mit.edu › courses-programs › mit-openFree Online Courses from MIT OCW | Open Learning

   openlearning.mit.edu › courses-programs › mit-open

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   MIT OpenCourseWare (OCW) is a free, publicly accessible, openly-licensed digital collection of high-quality teaching and learning materials, presented in an easily accessible format. Browse through, download and use materials from more than 2,500 MIT on-campus courses and supplemental resources, all available under a Creative Commons license ...

6. ocw.mit.edu › collections › most-popular-coursesMost Popular Courses | MIT OpenCourseWare | Free Online ...

   ocw.mit.edu › collections › most-popular-courses

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   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

7. ocw.mit.edu › courses › 6-036-introduction-toIntroduction to Machine Learning - MIT OpenCourseWare

   ocw.mit.edu › courses › 6-036-introduction-to

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   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.