Udacity’s Introduction to Machine Learning course covers foundational machine learning and data analysis.
Andrew Ng’s Machine Learning at Stanford University
This Coursera course teaches supervised machine learning, regression, and classification with Python.
About Andrew Ng’s Machine Learning at Stanford University
This Coursera course is the first part of the Machine Learning Specialization created with DeepLearning.AI and Stanford Online. It teaches supervised machine learning, including linear regression for prediction and logistic regression for binary classification, using Python with NumPy and scikit-learn.
It contains 3 modules with videos, readings, assignments and ungraded labs using Jupyter notebooks. The listed schedule is 3 weeks at 10 hours a week with self-paced learning and 9 assignments. Enrolling in the course also enrolls the learner in the full Specialization.
Key features
- Build supervised models in Python with NumPy and scikit-learn
- Train linear regression models for prediction tasks
- Train logistic regression models for binary classification
- Practice in Jupyter notebooks with ungraded labs
- Complete 9 assignments across 3 modules
- Earn shareable certificate for LinkedIn profile
Best for: Beginners who want to learn supervised regression and classification with Python.
Good for
- Beginner level with flexible, self-paced schedule
- Hands-on assignments and ungraded labs with Jupyter notebooks
- Shareable certificate that can be added to LinkedIn
Andrew Ng’s Machine Learning at Stanford University at a glance
- Category
- Education & Learning › AI Learning & Guides
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Andrew Ng’s Machine Learning at Stanford University FAQ
How long does the course take?
The listed schedule is 3 weeks at 10 hours a week, with learning at your own pace.
What tools are used in the course?
Python programming with NumPy, scikit-learn and Jupyter notebooks.
Does the course include a certificate?
Yes, it offers a shareable certificate that can be added to a LinkedIn profile.
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