Massachusetts Institute of Technology · on edX

Machine Learning with Python: From Linear Models to Deep Learning

Advanced 150 hours English MicrocredentialFREE
Our recommendation
MIT's serious, graduate-adjacent treatment of machine learning on edX: linear models, kernel machines, neural networks and reinforcement learning, taught through hands-on Python projects rather than a survey of buzzwords. Part of MIT's MicroMasters in Statistics and Data Science. Demanding and rigorous — for people with strong maths and Python who want real depth.

Good for: A rigorous, graduate-level machine-learning course from MIT.

Less suitable if: You want a gentle intro, or lack strong maths and Python.

Skills you'll gain

Machine learningLinear modelsNeural networksReinforcement learningPythonDeep learning

Is this course right for you?

A good fit if you…

You have strong maths and Python
You want real depth
You are pursuing the MITx MicroMasters

Consider something else if you…

You want a gentle introduction
Your maths or Python is shaky
You want a quick overview

Requirements: Strong linear algebra, calculus, probability and Python.

Realistic time: Around 13–15 weeks, significant weekly effort.

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.

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

What it costs

You can audit the course free on edX. A verified certificate is a paid option, with financial assistance available. A verified certificate (typically a few hundred dollars) is part of MIT's MicroMasters in Statistics and Data Science, which can count toward credit at MIT and other universities.

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Is the certificate recognised?

A verified MITx certificate on edX, part of MIT's MicroMasters in Statistics and Data Science — a rigorous, well-regarded credential that can count toward academic credit, though it is not itself a degree.

Instructor

I
Instructor
edX instructor

Taught by MIT faculty as part of the MITx MicroMasters in Statistics and Data Science.

About this provider

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Frequently asked questions

Very — it is graduate-adjacent, assuming strong linear algebra, calculus, probability and Python. It is not a gentle introduction.
Yes — you can audit it free on edX; the verified certificate is a paid option.
Yes — it is part of MIT's MicroMasters in Statistics and Data Science, which can count toward university credit.
Yes — it is taught through hands-on Python projects rather than a survey of concepts.
Around 13–15 weeks with significant weekly effort.
Free
to audit
Enroll now