Stanford free online courses with certificates: three different answers
Whether a free Stanford course gives you a certificate depends on which of three sources it comes from. A few short Stanford Medicine courses award one at no cost, the StanfordOnline courses on edX sell theirs, and the Stanford Engineering Everywhere lecture courses give none.
Free certificate: the Stanford Medicine continuing-education courses
Stanford Center for Continuing Medical Education lists these activities with a registration fee of free. When you finish, a claim-credit link takes you to Stanford's MY CE portal; complete the evaluation and you can view, print or email the certificate. Physicians receive AMA PRA Category 1 credit and everyone else the same hours as non-physician participation credit. There is no public verification link.
- Introduction to Food & Health: about 2.5 hours on edX in an audit-only track, 2.5 credit hours
- Identifying Early Signs of Psychosis in Adolescents and Young Adults: about 2 hours on edX, 2 credit hours
- Communicating with Presence: a module of about 1 hour on edX, 0.25 credit hours
- Unconscious Bias in Medicine: 1 hour on Stanford's own CME site, with a pre-test and post-test
- Empowering Teens with Healthier Sleep: a recorded talk of about 1.5 hours, 1.5 credit hours
Paid certificate: StanfordOnline courses on edX
These four courses can be audited at no cost, which gives you the videos and most materials but not graded assignments or a certificate, and edX limits audit access to the period the course is active, generally a few weeks to a few months. Paying for the verified track buys unlimited access, graded work and an edX certificate at the price on the course page.
- Computer Science 101: $249, six weeks at 4 to 6 hours a week, beginner
- Statistical Learning with Python: $186, eleven weeks at 3 to 5 hours a week, beginner
- Algorithms: Design and Analysis, Part 1: $189, six weeks at 2 to 4 hours a week, intermediate
- Mining Massive Datasets: $149, seven weeks at 5 to 10 hours a week, advanced
No certificate: Stanford Engineering Everywhere
Stanford Engineering Everywhere, or SEE, released nine complete computing and electrical engineering courses under a Creative Commons BY-NC-SA licence. Each carries the campus course as taught: every lecture on video with a transcript, the handouts, assignments, exams and, in most cases, the solutions. Stanford states that SEE is free, needs no registration, gives no credit and offers no feedback or contact with instructors. The pilot has ended, so nothing new will be added.
How to start a Stanford course for free
None of these routes involves applying to Stanford University.
- For a SEE course, open its page on see.stanford.edu and stream or download the first lecture; there is no account and nothing to enrol in.
- For a StanfordOnline course, open the edX page and choose the audit option, then note when the run ends, because your access stops there.
- Upgrade on edX only if you need graded assignments, permanent access or the certificate.
- For a Stanford Medicine course, launch it from the Stanford CME listing, complete it, then follow the claim-credit link to the MY CE portal.
- Read the prerequisites first; SEE and the advanced edX courses assume real background.
What you can study at Stanford for free
Most of what is listed is computing, engineering mathematics and a few short medical courses; business, humanities and languages are absent.
Computer science and programming
The SEE trio is the full first-year sequence. CS106A - Programming Methodology teaches Java from scratch over 28 lectures and asks for no prior programming, only hard work. CS106B - Programming Abstractions moves to C++ for data structures, recursion and complexity. CS107 - Programming Paradigms then covers memory management, functional programming and concurrency for people already comfortable in C++.
If you have never studied computing, Computer Science 101 on edX runs entirely in the browser with nothing to install. Tim Roughgarden's Algorithms: Design and Analysis, Part 1 assumes you can already code in Python, Java or C. Other universities are on the computer science hub.
AI, machine learning and data
CS229 - Machine Learning is Andrew Ng's graduate course on SEE: twenty lectures across supervised and unsupervised learning, learning theory and reinforcement learning, with notes and problem sets. It expects programming, basic probability and basic linear algebra. Statistical Learning with Python on edX follows the authors' own textbook from regression to deep learning with Python labs. Mining Massive Datasets covers MapReduce, PageRank and recommendation systems at graduate level. CS223A - Introduction to Robotics needs only matrix algebra. See also the AI certifications page.
Engineering mathematics
Four SEE courses serve engineers; each page lists its own maths prerequisites. EE261 - The Fourier Transform and its Applications has thirty lectures plus nine problem sets with solutions. EE263 - Introduction to Linear Dynamical Systems is Stephen Boyd's applied linear algebra course, and his EE364A - Convex Optimization I and EE364B - Convex Optimization II form a sequence, the second requiring the first. Other universities are on the mathematics hub.
Why Stanford's own free catalogue is not listed here
Stanford lists many free courses on online.stanford.edu, but that site sits behind a bot check that cannot be read reliably, so its course pages could not be verified. This site lists only Stanford courses whose cost and certificate terms were read directly on SEE, edX or the Stanford CME pages. If a course you expected is missing, that is why.