Program profile · official sources
Machine Learning (XCS229)
XCS229 Machine Learning is a Stanford School of Engineering professional course with prerecorded lectures, scheduled coursework and live sessions, taught by Tengyu Ma and Christopher Ré. It gives a broad introduction to machine learning and statistical pattern recognition: supervised learning, kernels and support vector machines, unsupervised learning, component analysis, deep learning basics and learning theory, with algorithms built from scratch. The listed session runs Nov 16 - Feb 7, 2027 at 10-15 hours per week. A score of 70% or higher on required assignments earns a Certificate of Achievement. An application checks Python, calculus, linear algebra and probability. It is an AI Professional Program course. As shown in the United States on 5 October 2026, tuition is USD 2,045.
Facts checked 5 Oct 2026
- Price
- USD 2045
- As shown in the United States on 5 October 2026, the official course page displays Tuition $2,045.00 for an individual enrollment in the Nov 16 - Feb 7, 2027 session; group pricing for five or more is by request. Taxes are not stated.
- Provider link
See price and enroll at Stanford Online (official site) ↗
Official site. No commission.
- Time
- Nov 16 - Feb 7, 2027 session listed; 10-15 hours per week (provider-listed); 10 CEU-equivalent units
- Level
- Not listed
- Credential
- Certificate of Achievement
Not stated on the captured course page.
- Prerequisites
- A short application (15 min) is required before your first course in the AI Professional Program, to demonstrate proficiency in Python (some assignments use basic Linux command line workflows), college calculus and linear algebra, and probability theory. Prior NumPy experience is recommended.
- Format
- 100% online, on-demand, live: prerecorded lectures with coursework on a set schedule and live online sessions with the teaching team; instructor-paced cohort
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
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See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Deep Learning
- Generative Learning Algorithms
- Kernels
- Learning Theory
- Principal and Independent Component Analysis
- Supervised Learning
- Support Vector Machines
- Unsupervised Learning
Prerequisites: A short application (15 min) is required before your first course in the AI Professional Program, to demonstrate proficiency in Python (some assignments use basic Linux command line workflows), college calculus and linear algebra, and probability theory. Prior NumPy experience is recommended.
What you actually do
- Deep Learning : Competency area listed on the course page / not a course module · Source
- Generative Learning Algorithms : Competency area listed on the course page / not a course module · Source
- Kernels : Competency area listed on the course page / not a course module · Source
- Learning Theory : Competency area listed on the course page / not a course module · Source
- Principal and Independent Component Analysis : Competency area listed on the course page / not a course module · Source
- Supervised Learning : Competency area listed on the course page / not a course module · Source
- Support Vector Machines : Competency area listed on the course page / not a course module · Source
- Unsupervised Learning : Competency area listed on the course page / not a course module · Source
What the credential is
- Credential type
- Certificate of Achievement · online.stanford.edu / xcs229-machine-learning
- Credential
- Certificate of Achievement · online.stanford.edu / xcs229-machine-learning
- Issuer
- Stanford School of Engineering (Stanford Online) · online.stanford.edu / xcs229-machine-learning
- Sharing
- Not stated on the captured course page. · online.stanford.edu / xcs229-machine-learning
- Exam requirement
- Complete the required assignments and receive a score of 70% or higher for the course. No separate certification exam is stated. · online.stanford.edu / xcs229-machine-learning
Total cost to finish
Estimate for the stated payment scope: USD 2045 × 1 = USD 2045.
- Individual enrollment (one course session): USD 2045 × 1 = USD 2045. One individual enrollment in the listed session as displayed on the official course page. · Source
Scope: Displayed tuition only; taxes and refund terms are not stated on the captured page. · Source
Who should skip it
- Course access is time-limited: course materials are available for 90 days after the course ends. · Official source · 2026-10-05
- Not for learners without Python, college calculus, linear algebra and probability: an application before the first AI Professional Program course checks these. · Official source · 2026-10-05
Alternatives in the registry
Related by topic or level.
- Deep Learning Specialization : Check official price; Overview: 3 months at 10 hours a week. FAQ: at 5 hours a week, each course typically takes 5 weeks except course 3, which takes about 4 weeks. These are separate provider estimates; no combined completion promise is inferred..
- Natural Language Processing Specialization : Check official price; Overview: 3 months at 10 hours a week. FAQ: at 5 hours a week, each course typically takes 4 weeks. These are separate provider estimates; no combined completion promise is inferred..
- Designing and Building AI Products and Services : Check official price; 10 weeks, online + live online, 6 hours per week (provider-listed).
Change log
- : Initial record from the official course page and the AI Professional Program page captured from the United States on 5 October 2026. · Source
See price and enroll at Stanford Online (official site) ↗
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