My AI Professor indexes AI courses, certificates and degrees from 55 providers — so a free Stanford lecture series sits right next to a premium Berkeley program, and you can pick the one that fits your goals and budget.
Indexing courses and programs from
Fifteen categories cover the whole landscape, from your first AI literacy course to a graduate degree. Every category lists free and paid options together.
Understand what AI is, how it works, and how to use it — no coding required.
Transformers, large language models, fine-tuning, and building with foundation models.
Write prompts that reliably get the results you want from any model.
Build agents, use the Model Context Protocol, and ship with vendor SDKs.
Build real software by working with AI coding agents, even if you are new to code.
Wire AI into your daily work and business with no-code automation and agents.
Supervised and unsupervised learning, model evaluation, and the math behind it.
Text processing, embeddings, sequence models, and modern transformer NLP.
Image classification, object detection, segmentation, and generative image models.
Markov decision processes, policy gradients, deep RL, and robotics applications.
Linear algebra, statistics, calculus, Python, and data analysis for AI work.
Deployment, monitoring, data pipelines, and engineering practices for real AI systems.
Executive education and strategy courses for leaders deploying AI.
Fairness, alignment, governance, and the societal impact of AI.
AWS, Microsoft Azure, Google Cloud, IBM, NVIDIA and other industry credentials.
Online master's degrees, graduate certificates, and MicroMasters in AI.
We never hide the free option behind the expensive one. World-class free courses are listed alongside premium executive programs so you can decide what the credential, cohort and support are worth to you.
Well-taught, up-to-date, and respected by employers. A good first stop if you're not sure where to begin.
Andrew Ng's updated three-course sequence covers regression, classification, neural networks, decision trees, clustering, and recommender systems in Python. Take it as the canonical first ML course if you want a rigorous but gentle on-ramp with hands-on labs.
Jeremy Howard's top-down course has you training state-of-the-art image, text, and tabular models in lesson one, then peels back the layers to the math. Ideal for working programmers who want results first and theory second.
Anthropic's comprehensive developer course spanning API setup, prompt evaluation, tool use, RAG, extended thinking, prompt caching, MCP, and agent workflows like routing and parallelization. The go-to course for Python developers who want to build production apps on Claude.
A non-technical introduction to what AI is, what it can and cannot do, and how it affects society, built by the University of Helsinki and taken by over a million learners. Take it if you want a trustworthy, university-backed AI literacy foundation with zero math or coding required.
Covers agent fundamentals (tools, reasoning, actions), then builds agents with smolagents, LangGraph, and LlamaIndex, finishing with a benchmark challenge and leaderboard. For Python developers who want framework-agnostic agent skills and a free certificate.
A foundational AWS certification validating knowledge of AI/ML and generative AI concepts, AWS AI services (Bedrock, SageMaker) and responsible AI. Designed for business analysts, project managers and sales or product staff who work alongside AI builders rather than build models themselves.
The companies building the models publish their own free courses. These are the fastest way to learn the tools as their makers intend them to be used.
Anthropic's 4D framework (Delegation, Description, Discernment, Diligence) for working with AI effectively, efficiently, ethically and safely, developed with professors Joseph Feller (University College Cork) and Rick Dakan (Ringling College). For anyone from first-time users to experienced practitioners who wants a tool-agnostic way to decide what to hand to AI and how to check its work.
OpenAI's entry course on how AI and large language models work, built around improving one real task you do regularly with clear instructions, context, output review and responsible use. For people new to AI at work who want the first step of OpenAI's Apply AI at Work track, with no technical background needed.
Pick a workflow you perform regularly, break it into steps, identify where ChatGPT can help, and build a practical plan with review points built in. For people who already use AI for one-off tasks and want to apply it consistently; OpenAI recommends AI Foundations first.
A practical tour of using Claude at work: first conversations, getting better results, Projects, Artifacts, Skills, connecting tools, enterprise search and Research, plus use cases by role. A good first course for anyone whose team has adopted Claude and who wants a vendor-made orientation with a certificate.
A two-hour course from Google showing middle and high school teachers how to use Gemini to save time on planning, differentiate instruction, and teach AI responsibly. Take it if you teach and want a fast, free, classroom-focused start with a PD-eligible certificate.
OpenAI's free course tracks: Apply AI at Work (foundations, applied workflows, agents), Build with AI (Codex and the OpenAI API), Lead AI Adoption, and Teach and Learn with AI. A vendor-direct option for anyone who wants to learn ChatGPT, Codex, and agent workflows from OpenAI itself.
Curated sequences that take you from zero to a real skill, mixing the best free material with optional paid credentials.
Understand how modern AI works, use it well at work, and know enough to talk with technical teams. No coding.
The classic route: Python and math foundations, then the Stanford/DeepLearning.AI curriculum, then deep learning and shipping models to production.
Go from calling a model API to building agents with tool use and MCP, using official training from Anthropic, Hugging Face and Microsoft.
Yes. We reserve the Free label for courses with no payment at any point. Courses where the videos are free but the certificate costs money are labeled “Free to audit” so you always know the deal before you click.
Most can be audited free: you can watch all lectures and read all materials. You pay (typically $49–$79 per course, or a Coursera Plus subscription around $59/month) only for graded assignments and a shareable certificate. Financial aid is available on both platforms.
Not automatically. You pay for structure, a cohort, instructor access, deadlines and a brand-name credential. If you have the discipline to self-study, the free university lecture series on this site are often the same material. We list both so you can decide what the extras are worth to you.
Each listing records a last-verified date. We check the provider's page directly and quote the price shown there. Prices change often, so confirm before you enroll and tell us if something is out of date.
No. We don't sell courses or charge enrollment fees, and no provider pays for placement. If that ever changes it will be disclosed on the About page and will never affect rankings.
Begin with the AI Foundations category or the “AI-literate professional” learning path. If you can code, go straight to Machine Learning or the “Zero to ML engineer” path. If you lead a team, see AI for Business & Leadership.
The index grows by community suggestion. Tell us about a course, bootcamp, certificate or degree and we'll review and add it.