The short answer
Yes, you can take real AI courses from Harvard, MIT and Stanford for free. Harvard's best known option is CS50's Introduction to Artificial Intelligence with Python, which you can study free and which even offers a free CS50 certificate if you pass the projects. MIT puts full course materials, including lecture videos, on MIT OpenCourseWare with no enrolment. Stanford publishes free lecture series through Stanford Engineering Everywhere and on YouTube for courses such as CS224N and CS25.
The catch is that almost all of it is built for people who can code, and several courses expect university maths. If you want to understand and use AI in your job rather than build it, only a small part of this material is aimed at you, and we point to those parts below.
Checked against each provider's own pages on 28 September 2026. Offers change, so confirm the current details before you enrol. Sources: Harvard free courses, Harvard AI courses, CS50 AI, MIT OpenCourseWare, Stanford Engineering Everywhere, Stanford CS224N and Stanford CS25.
The courses at a glance
| Course or resource | Provider | What it covers | Level and technicality | Free or paid | Certificate |
|---|---|---|---|---|---|
| CS50's Introduction to Artificial Intelligence with Python | Harvard (via edX) | Search, optimisation, machine learning, large language models | Intermediate; needs Python | Free to study | Free CS50 certificate if you pass the projects; paid edX verified certificate |
| Machine Learning and AI with Python | Harvard (via edX) | Decision trees, random forests, bias, overfitting | Intermediate; builds on Python | Free to audit | Paid verified certificate |
| Generative AI: How to Use It and Why It Matters | Harvard Kennedy School | Using and understanding generative AI | Listed as intermediate; aimed at professionals | Paid | Certificate of completion |
| Artificial Intelligence (6.034) | MIT OpenCourseWare | Classic AI: knowledge representation, problem solving, learning | Undergraduate; programming assignments | Free | None |
| Foundation Models and Generative AI (6.S087) | MIT OpenCourseWare | History of AI, foundation models, generative AI | Described by MIT as non-technical | Free | None |
| Hands-On Deep Learning (15.773) | MIT OpenCourseWare | Neural networks, transformers, LLMs, text-to-image | Graduate; needs Python and machine learning basics | Free | None |
| CS229 Machine Learning | Stanford Engineering Everywhere | Supervised and unsupervised learning, learning theory | Needs probability and linear algebra | Free | None mentioned |
| CS224N: NLP with Deep Learning | Stanford (lectures on YouTube) | Language models and deep learning for text | Needs Python, calculus, linear algebra | Free videos | None for public viewers |
| CS25: Transformers United | Stanford | Research talks on transformers and LLMs | Seminar talks; no prerequisites listed | Free to audit | None for public viewers |
Harvard's free AI courses
Harvard's online catalogue lists AI courses at very different prices, from free to five figures for on-campus executive programmes, so read the price line on each page. Its free catalogue marks free courses with an asterisk, and the AI subject page notes that free courses may have optional paid components.
CS50's Introduction to Artificial Intelligence with Python is the famous one. According to the course page, it runs for 7 weeks at 10 to 30 hours per week, is rated intermediate, and is free to audit, with a verified edX certificate listed at $299 (prices can vary by country). The CS50 AI site lists the topics as graph search algorithms, classification, optimisation, machine learning and large language models, and the prerequisite as CS50x or at least a year of Python experience.
The detail most people miss is on the certificate page: if you submit every project and score at least 70% on each, you are eligible for a free CS50 Certificate. The paid edX certificate is a separate option. So for someone who already codes, this is one of the best free AI courses there is, certificate included.
Machine Learning and AI with Python is also free to audit, at 4 to 5 hours per week, with a $299 verified certificate as an add-on. It focuses on decision trees and related methods, and it expects you to build on existing Python experience.
For non-coders, the honest picture is that Harvard's non-technical AI courses are paid. The Kennedy School's Generative AI: How to Use It and Why It Matters is listed at $1,995 for six weeks, and the subject page lists lower-priced business courses such as Future Proof with AI at $199. Those may be worth it for some people, particularly with an employer paying, but they are not free.
"Free to audit" usually means free to watch and study. Graded work, the verified certificate or both can sit behind a payment. Check which parts are free before you commit weeks to a course.
MIT's free AI courses on OpenCourseWare
MIT's offer is simpler. MIT OpenCourseWare describes itself as a free and open collection of material from thousands of MIT courses, with no enrolment and always available. It is equally clear about the trade-off: MIT does not offer credit or certification to users of OCW. You get the real course materials, not a course experience with deadlines and marking.
For searches like "MIT AI courses free", these are the ones worth knowing:
- Artificial Intelligence (6.034, Fall 2010), taught by Patrick Henry Winston, with lecture videos, recitation videos, programming assignments and exams. It is older, and it teaches the classic foundations rather than today's chatbots.
- Introduction to Machine Learning (6.036, Fall 2020), covering modelling, prediction, overfitting, supervised learning and reinforcement learning. Undergraduate level and mathematical.
- Hands-On Deep Learning (15.773, Spring 2024) from MIT Sloan, a graduate course covering neural networks, transformers, large language models and text-to-image models. It asks for prior familiarity with Python and basic machine learning ideas.
- Foundation Models and Generative AI (6.S087, January 2024), a lecture series that MIT itself calls non-technical, with the line "All backgrounds are welcome." If you are not a developer and want an MIT lecture on how modern AI came about, start here.
There is also Generative Artificial Intelligence in K-12 Education (6.S062), which is worth a look for teachers, though it is a project-based university class rather than a quick guide.
Stanford's free AI courses and YouTube lectures
Stanford's free material is spread across a few places. Stanford Engineering Everywhere says it offers Stanford course material online at no charge, needing only a computer and an internet connection. Its best known AI course is CS229 Machine Learning, taught by Andrew Ng, with 20 lecture videos, lecture notes and problem sets with solutions. The listed prerequisites are basic computer science plus familiarity with probability theory and linear algebra, which tells you the level.
For "Stanford AI courses on YouTube", the course pages themselves point to the recordings:
- The CS224N page (Natural Language Processing with Deep Learning) says complete videos are available free on the CS224N 2024 YouTube playlist. The same page lists proficiency in Python, college calculus, linear algebra and basic probability as prerequisites.
- The CS25: Transformers United page says anyone is free to audit in person or join the Zoom livestreams without signing up or being affiliated with Stanford, and recordings are posted on the course website. These are research talks, so they are more accessible than a problem set but still assume some interest in how models work.
The current CS229 page for Summer 2026 does not link public videos, so the Engineering Everywhere recordings are the free route for that course.
In plain English
- Audit:
- Taking a course for free without the paid extras, which usually means no graded certificate.
- OpenCourseWare:
- MIT's free publication of real course materials. You study alone, with no enrolment, marking or certificate.
- Prerequisite:
- Something the course assumes you already know. For most university AI courses, that means Python and some maths.
Which one should you actually take?
If you can already program in Python and want to build AI systems, take CS50 AI. It is free, well structured and comes with a free certificate if you pass the projects. After that, MIT's Hands-On Deep Learning or Stanford's CS224N lectures are strong next steps. In this case the famous option really is the better choice, and nothing we offer replaces it.
If you want the theory and do not mind maths, Stanford's CS229 and MIT's 6.036 are the classic foundations.
If you do not code and want to understand modern AI, watch MIT's non-technical Foundation Models and Generative AI lectures, then pick a course built around using AI at work. The rest of this list will mostly feel like the wrong course, and that says nothing bad about you. Our guide on how to choose a free AI course explains why the use-or-build question matters more than the brand.
Where LearnWithZavi fits
LearnWithZavi is a free AI school for people who are not developers. There is no signup and no payment stage, lessons are short and browser-based, and you can print a free certificate of completion when you finish a course. We are not affiliated with Harvard, MIT or Stanford, and we are not an accredited institution, so our certificate records that you finished the lessons rather than being a formal qualification.
Good places to start:
- Introduction to Generative AI, the plain-English version of what the university lectures explain
- Prompt Engineering, for getting better answers from AI tools at work
- Free AI courses with a certificate, courses that need no coding and generative AI courses
- The full list of free AI courses
If you want a university name on your CV, the certificate question matters. Our post on free AI courses with certificates covers what different certificates are worth.
Frequently asked questions
Are Harvard's AI courses really free? Some are. CS50's Introduction to Artificial Intelligence with Python and Machine Learning and AI with Python are free to audit, and CS50 AI offers a free CS50 certificate if you score at least 70% on each project. Harvard's non-technical AI courses for professionals, such as the Kennedy School generative AI course, are paid.
Does MIT OpenCourseWare give a certificate? No. MIT says it does not offer credit or certification to OCW users. The materials are free and need no enrolment, but you study on your own.
Are there free Stanford AI courses on YouTube? Yes. The CS224N course page links complete lecture videos on YouTube, CS25 posts its recordings, and Stanford Engineering Everywhere hosts CS229 lecture videos free of charge.
Do I need to know how to code? For most of these courses, yes. CS50 AI needs Python, and Stanford's CS229 and CS224N need maths as well. MIT's Foundation Models and Generative AI lectures are the clearest exception, as MIT describes them as non-technical.
Is a free certificate from these universities worth having? The free CS50 certificate shows you completed demanding projects, which carries weight with technical employers. It is not a degree or academic credit, and MIT OpenCourseWare offers no certificate at all.