Machine LearningBeginner
Machine Learning Crash Course
Google's fast-paced introduction to machine learning. Covers ML concepts, TensorFlow APIs, and real-world case studies. Written and maintained by Google engineers. Completely free.
Free course on MIT OpenCourseWare
Machine Learning (MIT 6.867)
100 hours 4.8(5,100 reviews)Free
MIT's Machine Learning course (6.867) is a rigorous, advanced course available free on OpenCourseWare. It covers supervised learning, unsupervised learning, and statistical foundations from a theoretical perspective. The course uses MIT's teaching materials: lectures, problem sets, and exams. After finishing, you understand the mathematics behind ML algorithms. This is not for beginners. The main limitation: MIT's pace is fast. Expect 20+ hours per week of work if you do all problem sets and the exam.
About This Course
MIT's graduate-level machine learning course. Covers supervised and unsupervised learning, neural networks, SVMs, Bayesian methods, EM algorithm, and reinforcement learning.
Course Details
- Platform
- MIT OpenCourseWare
- Language
- Machine Learning
- Level
- advanced
- Duration
- 100h
- Certificate
- No
- Cost
- Free
Frequently Asked Questions
Is MIT's ML course free?
Yes, free on MIT OpenCourseWare.
Is it for beginners?
No. You need linear algebra, calculus, probability, and Python proficiency.
Should I take this or Andrew Ng's course?
Ng first (intuition), then MIT (rigor). MIT goes much deeper into the math.
Is the problem sets required?
Not required, but highly recommended. The problem sets are where the real learning happens.
How long does this take?
If you do all the work, expect 15-20 weeks at 20+ hours per week.
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