Free AI Courses From Harvard, MIT and Stanford (and Which Give a Certificate)

You can take real AI courses from Harvard, MIT and Stanford for free. 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.

Which Harvard, MIT and Stanford AI courses are free?

Is Harvard's AI course free with a certificate?

Harvard's online catalogue lists AI courses at very different prices, from free to several thousand dollars for executive programmes, so read the price line on each page. On the AI subject page, free courses are marked "Free" with an asterisk, which in practice means the course is free to study but has a paid add-on, usually a verified certificate.

CS50's Introduction to Artificial Intelligence with Python is the famous one, and the main reason people search for a free Harvard AI course with a certificate. According to the course page, it runs for 7 weeks at 10 to 30 hours per week, is self-paced, is rated intermediate, and is free to audit, with a verified edX certificate listed at $299. The CS50 AI site splits the course into seven weeks: search, knowledge, uncertainty, optimisation, learning, neural networks and language. It lists the prerequisite as CS50x or at least one year of experience with Python.

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. That is a separate thing from the paid edX verified certificate. So for someone who already codes, this is one of the best free AI courses there is, certificate included.

Be clear about what that certificate is. The CS50 AI FAQs say both the free and the verified certificates "are not accredited academic offerings" from Harvard. For accredited credit, CS50 points you to the paid Harvard Extension School version.

If the Python requirement puts you off, you are not alone. Our guide to what you need before learning AI explains which skills actually matter, and AI coding for non-programmers shows how far you can get without learning to code first.

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 starts with decision trees and builds towards random forests and gradient boosting, and it expects existing Python experience. Unlike CS50 AI, there is no separate free certificate.

Fundamentals of TinyML is listed at $0 on Harvard's catalogue. It is an introductory course at 2 to 4 hours per week about machine learning on tiny devices, with a $299 verified certificate as an option. It suits people curious about engineering and hardware more than office workers.

For non-coders, the honest picture is that Harvard's non-technical AI courses are paid. These are easy to mistake for free courses because they sit on the same catalogue pages:

• The Kennedy School's Generative AI: How to Use It and Why It Matters is listed at $1,995 for six weeks.
• Harvard Business School Online's AI Essentials for Business is listed at $1,949 for four weeks at 5 to 7 hours a week.
• The subject page also lists shorter paid courses, such as Agentic AI Foundations at $595.

Those may be worth it for some people, particularly with an employer paying, but they are not free.

How do you get the free CS50 AI certificate?

This is the route to a free CS50 certificate, based on the CS50 AI FAQs. It is not an accredited Harvard qualification, and it takes real work: the FAQs suggest 10 to 20 hours for each week's assignments.

1. Register on edX and pick the free option. CS50 says edX registration is required for either certificate. Choose the "free" or "audit" option, which needs no payment, unless you want the $299 verified certificate.
2. Work through the 7 weeks at cs50.harvard.edu/ai. Watch each lecture, then complete that week's project. There are no weekly deadlines.
3. Submit every project and pass each one. You submit with your GitHub account, and each project needs at least 70%. Watching the videos alone does not count. You can resubmit; only your latest submission counts.
4. Request the certificate from your Gradebook. Your CS50 AI Gradebook is linked to your edX account. Once every project is passed, a link to request the free certificate appears within about four hours. Log in with GitHub and download the certificate before the course deadline.

When we checked, the course deadline was 30 June 2027 (end of day UTC). CS50 may extend it but makes no exceptions, so do not leave the last project to the final week.

Does MIT have free AI and generative AI courses?

MIT has two free routes now: OpenCourseWare, which publishes real course materials, and MIT Learn, which hosts newer self-paced courses including the Universal AI programme.

Foundation Models and Generative AI (6.S087) is MIT's free generative AI course for everyone. It is a January 2024 lecture series that MIT itself calls non-technical, with the line "All backgrounds are welcome." It runs from a short history of AI to foundation models, with applications in science and business. If you are not a developer and want an MIT lecture on how modern AI came about, start here.

Fundamentals of Programming and Machine Learning is the free first course in MIT's Universal AI programme. It is self-paced, at 3 to 4 weeks of 4 to 8 hours a week, and MIT says no coding background is needed. It introduces Python, data and machine learning, but the code is provided, so you read and run it rather than write it. There is no certificate for this free course.

The rest of Universal AI is paid. The other four required courses (deep learning, decision-making, large language models, and AI ethics) cost $300 each, each with an MIT Open Learning certificate of completion. The full programme is $899, against $1,200 bought separately.

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 OCW courses are also 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.

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.

Are Stanford's AI courses free?

Stanford's free material is lecture videos, not courses with marking. Its AI programmes FAQ says there is no financial aid or discount for individuals, but anyone can watch lecture videos free, including on the Stanford Online YouTube channel.

CS229 Machine Learning is the best known. The free full course is the Autumn 2018 YouTube playlist led by Andrew Ng. Another Andrew Ng version, with notes and problem sets, is free on Stanford Engineering Everywhere. If you want the same teacher in a gentler format, our guide to whether DeepLearning.AI courses are free covers Andrew Ng's beginner courses.

The for-credit CS229 runs through Stanford Online as a paid course. Its course page did not show a price when we checked on 9 November 2026, so confirm the current fee with Stanford before you plan around it. Stanford says it does not offer financial aid or discounts to individuals.

CS224N (Natural Language Processing with Deep Learning) is the course to watch if you want to understand how language models work. The CS224N page says complete videos are available free on the CS224N 2024 YouTube playlist. The paid route is XCS224N, the Stanford AI Professional Program version, which anyone can join for a fee and which comes with a certificate. Prerequisites are Python, college calculus, linear algebra, probability and some machine learning.

CS25: Transformers United is the most open of the three. The CS25 page says anybody can audit in person or join the Zoom livestreams without signing up, 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.

What is the difference between the free and paid certificates?

"Certificate" means very different things on these pages.

So CS50 AI is the only free university-branded certificate here, and it needs real coding. For a free certificate without coding, big tech providers often fit better: see Google's free AI courses, Microsoft's free AI courses and free AI courses from NVIDIA, IBM and AWS.

Which one should you 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, or take MIT's free Universal AI course 1. 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 to AI for non-technical people is written for exactly this situation.

If you want a full free plan rather than one course, our guide on how to learn AI for free puts university lectures alongside practical options, and our guide on how to choose a free AI course explains why the use-or-build question matters more than the brand.

Where does LearnWithZavi fit?

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.