EDMassachusetts Institute of Technology · on edX
Machine Learning with Python: From Linear Models to Deep Learning
Advanced 150 hours English Verified CertificateFREE
About this course
This is MIT's serious, graduate-adjacent treatment of machine learning: linear models, kernel machines, neural networks, and reinforcement learning, taught through hands-on Python projects rather than a survey of buzzwords. It's part of MIT's MicroMasters program in Statistics and Data Science, so it's built to MIT's own academic standard, not a simplified industry overview.
The honest take: this is genuinely advanced — comfortable with linear algebra, probability, and real Python is assumed, not optional. If you want a gentler on-ramp to machine learning, look elsewhere first; if you want MIT-level rigor, this delivers it.
What you'll learn
Understand classification, regression, and clustering principles
Implement linear models, kernel machines, and neural networks
Apply reinforcement learning fundamentals
Choose suitable models for different ML problems
Run full ML projects: training, validation, tuning, feature engineering
Build a foundation equivalent to graduate-level ML coursework
This course includes
150h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
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Instructor
I
Instructor
edX instructor
— learners— courses — instructor rating
Taught by MIT faculty as part of the MITx MicroMasters in Statistics and Data Science.
Requirements
- Linear algebra
- Probability
- Solid Python programming experience
Who this course is for
- Learners with strong math and Python background
- MicroMasters in Statistics and Data Science candidates
About this provider
ED
edX
Non-profit online learning platform founded by Harvard and MIT. 45M+ learners worldwide.
4.5 trust score
Frequently asked questions
No — it assumes strong linear algebra, probability, and Python skills. Start with a beginner ML course first if you lack these.
Audit free; a verified certificate is available for a fee.
Around 150 hours — a serious, semester-length commitment.
Yes, it's a core course in MIT's MicroMasters in Statistics and Data Science.
Yes — it spans from classical linear models through neural networks and reinforcement learning.