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91 completely free AI courses

No credit card, no trial, no 'free to audit' fine print. Every course on this page is free from start to finish, including full university lecture series and official vendor training.

AI Foundations

Understand what AI is, how it works, and how to use it — no coding required.

All AI Foundations
Anthropic, with University College Cork and Ringling College·Anthropic Academy
Free

AI Fluency: Framework & Foundations

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.

beginner Self-paced (4 modules) Certificate
OpenAI·OpenAI Academy
Free

AI Foundations

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.

beginner ~70 minutes Certificate
OpenAI·OpenAI Academy
Free

Applied AI Foundations

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.

intermediate ~80 minutes Certificate
Microsoft·GitHub
Free

Artificial Intelligence for Beginners - A Curriculum

A 24-lesson open curriculum from Microsoft covering symbolic AI, neural networks, computer vision, NLP, and AI ethics with labs in TensorFlow and PyTorch. Suited to learners with some Python who want a structured, semester-style tour of AI fundamentals for free.

beginner 12 weeks (24 lessons)
Microsoft and LinkedIn·LinkedIn Learning
Free

Career Essentials in Generative AI by Microsoft and LinkedIn

A short learning path introducing generative AI concepts, ethical considerations, and tools like Microsoft Copilot, ending with a Microsoft-branded professional certificate. A quick, free credential for job seekers and office workers who want generative AI on their LinkedIn profile.

beginner ~4-6 hours (5 courses) Certificate
Anthropic·Anthropic Academy
Free

Claude 101

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.

beginner Self-paced (5 sections) Certificate
Harvard University·edX
Free

CS50's Introduction to Artificial Intelligence with Python

Harvard's project-driven course on the algorithms behind AI: graph search, knowledge, uncertainty, optimization, machine learning, neural networks, and language models, each with a hands-on Python project. For programmers with Python experience who want rigorous fundamentals and a Harvard-backed free certificate.

intermediate 7 weeks, self-paced Certificate
University of Helsinki and MinnaLearn·University of Helsinki
Free

Elements of AI: Introduction to AI

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.

beginner ~30 hours, self-paced Certificate
Google
Free

Generative AI for Educators with Gemini

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.

beginner ~2 hours Certificate
OpenAI·OpenAI Academy
Free

OpenAI Academy

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.

beginner 60-90 minutes per course, self-paced Certificate

Generative AI & LLMs

Transformers, large language models, fine-tuning, and building with foundation models.

All Generative AI & LLMs
Nir Diamant (DiamantAI)·GitHub
Free

Advanced RAG Techniques: Elevating Your Retrieval-Augmented Generation Systems

A large catalogue of runnable notebooks, each isolating one retrieval-augmented generation technique, from basic chunking and query transformations to reranking, hierarchical and graph-based retrieval, and evaluation. It suits developers who have built a basic RAG app and want to systematically try the techniques that improve retrieval quality.

intermediate 40+ runnable notebooks, self-paced
Google Cloud·Google
Free

Beginner: Introduction to Generative AI

Google Cloud's short beginner path explaining what generative AI and large language models are, how they work, and the principles of responsible AI. A fast, free badge-earning starting point for non-technical professionals before moving to Google's deeper developer paths.

beginner ~2 hours (4 activities) Certificate
Stanford University·YouTube
Free

CS25: Transformers United V6

Stanford's seminar series where leading researchers present the latest on transformers, LLMs, world models, state-space models, multimodal systems, and production inference. For practitioners and researchers who want to follow frontier work straight from the people doing it.

advanced Weekly seminar, Spring quarter (recordings available)
Microsoft·GitHub
Free

Generative AI for Beginners (Version 3) - A Course

Microsoft's 21-lesson course on building generative AI apps, with Learn and Build lessons covering prompting, RAG, embeddings, function calling, agents, fine-tuning, and security in Python and TypeScript. Great for developers who want a free, code-first path from LLM basics to deployable applications.

beginner 21 lessons, self-paced
Hugging Face
Free

Hugging Face LLM Course

Hugging Face's hands-on course on LLMs and NLP using the Transformers, Datasets, Tokenizers, and Accelerate libraries, from fundamentals through fine-tuning, demos, and reasoning models. Best for Python developers who want to work with open models directly rather than only via APIs.

intermediate 12 chapters, self-paced
Maxime Labonne·GitHub
Free

LLM Course

A widely starred roadmap in three tracks: optional fundamentals, the LLM Scientist (architecture, pre-training, fine-tuning, preference alignment, evaluation, quantization) and the LLM Engineer (running models, vector stores, RAG, agents, inference optimization, deployment, security). It suits self-directed learners who want a curated map of the best free resources plus runnable notebooks rather than one instructor's course.

intermediate 3 parts with curated readings and notebooks, self-paced
Cohere
Free

LLM University (LLMU)

Cohere's free learning hub of expert-led modules and guides on how LLMs work, text embeddings, semantic search, prompt engineering, RAG, and tool use, with code labs using Cohere's API. A practical choice for developers who want enterprise-oriented LLM skills explained clearly.

beginner Self-paced modules
DataTalks.Club·GitHub
Free

LLM Zoomcamp: Free Course on Building LLM Applications with RAG, Agents & Vector Search

A project-driven community course that goes from agentic RAG with function calling through vector search, orchestration, evaluation and monitoring to an end-to-end assistant and a capstone of your choice. It suits Python developers comfortable with Docker and the command line who want a complete, production-minded LLM application course with optional cohort deadlines and peer review.

intermediate 10 weeks Certificate
Andrej Karpathy·YouTube
Free

Neural Networks: Zero to Hero

Andrej Karpathy builds neural networks from scratch in code, starting with backpropagation and micrograd and ending with a GPT transformer and BPE tokenizer. For programmers comfortable with Python and intro calculus who want to truly understand how language models work under the hood.

intermediate 8 lectures (~15+ hours), ongoing
Parlance Labs (Hamel Husain and collaborators)·Parlance Labs
Free

Parlance Labs Educational Resources

A free library of practitioner talks and workshops from Hamel Husain's network, covering LLM evaluation, RAG fundamentals and systematic RAG improvement, building and deploying LLM apps, and a deep track on when and how to fine-tune. It suits engineers who already ship LLM features and want battle-tested advice on evals and reliability from people widely followed on X.

intermediate 27 talks and workshops

Prompt Engineering

Write prompts that reliably get the results you want from any model.

All Prompt Engineering
Anthropic·GitHub
Free

Anthropic's Prompt Engineering Interactive Tutorial

Anthropic's nine-chapter tutorial with exercises on prompt structure, roles, separating data from instructions, step-by-step thinking, few-shot examples, avoiding hallucinations, and building complex prompts. The definitive hands-on resource for anyone building with Claude.

intermediate 9 chapters, self-paced

AI Agents & Developer Tools

Build agents, use the Model Context Protocol, and ship with vendor SDKs.

All AI Agents & Developer Tools
HumanLayer (Dex Horthy)·GitHub
Free

12-Factor Agents - Principles for building reliable LLM applications

An influential essay series, modelled on the 12-Factor App, arguing for owning your prompts, context window and control flow, treating tools as structured outputs, and keeping agents small, stateless and pausable. It suits engineers moving agents from demo to production who want design principles rather than another framework tutorial.

intermediate 12 short chapters plus a bonus factor, a few hours of reading
Google·Kaggle
Free

5-Day Gen AI Intensive Course with Google

Google and Kaggle's intensive pairs a daily whitepaper with hands-on codelabs on foundation models, embeddings, agents, domain-specific LLMs, and MLOps using Gemini and the Agent Development Kit. For developers who want a dense, free bootcamp-style sprint through Google's GenAI stack.

intermediate 5 days (self-paced)
Hugging Face
Free

AI Agents Course

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.

intermediate ~15-20 hours (5 units plus bonus units) Certificate
Microsoft·GitHub
Free

AI Agents for Beginners - A Course

Microsoft's 18-lesson open course on agent design patterns, tool use, planning, multi-agent systems, agentic RAG, memory, trust and security, and protocols like MCP and A2A. For developers who want a free, vendor-documented survey of agent concepts with runnable samples.

beginner 18 lessons, self-paced
Geoffrey Huntley·GitHub
Free

Build Your Own Coding Agent via a Step-by-Step Workshop

A six-step workshop that grows a basic Claude chat program into a working coding agent by adding file reading, directory listing, shell execution, file editing and code search, explaining the agent event loop along the way. It suits developers comfortable with Go who want to demystify coding agents by writing a minimal one themselves.

intermediate 6-step workshop, a few hours
Anthropic·Anthropic Academy
Free

Building with the Claude API

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.

intermediate Self-paced (multi-module with final assessment) Certificate
Anthropic·Anthropic Academy
Free

Claude Code in Action

Shows developers how to run longer, less supervised Claude Code sessions: plan mode, CLAUDE.md, skills, permission modes, hooks, headless automation, GitHub Actions, and team plugins. For engineers already using Claude Code who want to move to team-wide, verifiable workflows.

intermediate Self-paced (4 modules) Certificate
Anthropic·Anthropic Academy
Free

Claude Platform 101

A ground-up introduction to the Claude Platform using the TypeScript SDK: first requests, model selection, agent loops, tool use, built-in tools, skills, MCP, and Managed Agents. For developers who have never used an LLM API and want the fastest route to a working agent.

beginner Self-paced (~12 lessons) Certificate
Anthropic·Anthropic Academy
Free

Claude with Amazon Bedrock

A long technical course on building with Claude through Amazon Bedrock: the API via boto3, prompt evaluation and engineering, tool use, RAG with embeddings and reranking, extended thinking, prompt caching, MCP, and agent design with Claude Code and computer use. For backend, ML and DevOps engineers on AWS who want a free end-to-end path to Bedrock-hosted Claude agents.

intermediate 85 lectures, ~8 hours of video, 10 quizzes Certificate
OpenAI·OpenAI Academy
Free

Design and Build Agentic Systems

Design multi-agent applications with clear roles, controlled tool access and reliable handoffs, then test the workflow against defined outcome and safety requirements in a guided lab. For developers with API experience who want OpenAI's own method for building agentic systems on its platform.

intermediate ~110 minutes (lessons plus guided lab) Certificate
Microsoft·Microsoft Learn
Free

Develop AI agents on Azure

Builds agents with Microsoft Foundry Agent Service and Microsoft Agent Framework: custom tools, MCP tools, knowledge grounding with Foundry IQ, publishing to Teams and Microsoft 365 Copilot, workflows, multi-agent orchestration and A2A discovery. For developers and AI engineers building agents on Azure who want Microsoft's free, code-first path (course AI-3026).

intermediate 9 modules, ~10 hours
Nir Diamant (DiamantAI)·GitHub
Free

GenAI Agents: Comprehensive Repository for Development and Implementation

A large, community-favourite collection of 64 runnable notebooks, from a beginner conversational agent to multi-agent research, business and QA systems, using LangGraph, PydanticAI, CrewAI, AutoGen, MCP and plain SDK code. It suits Python developers who learn best by reading and modifying working agent code across many frameworks.

intermediate 64 notebook tutorials, self-paced
LangChain·LangChain Academy
Free

Introduction to Deep Agents

Builds long-running agents with Deep Agents, LangChain's open-source agent harness: models, tools, MCP, human-in-the-loop, filesystem backends and sandboxes, summarization, skills and memory, subagent delegation, and a sales-assistant capstone in Python or TypeScript. For developers building complex multi-step agents who want LangChain's current recommended approach.

intermediate 46 lessons (~30 minutes of video plus hands-on labs)
LangChain·LangChain Academy
Free

Introduction to LangGraph - Python

LangChain's official LangGraph course: graphs, routers and agents, state and memory, streaming and human-in-the-loop breakpoints, parallelization and sub-graphs, long-term memory with the LangGraph Store, and deployment. For Python developers who want precise control over agent workflows, taught by the team that builds the framework.

intermediate ~6 hours of video (55 lessons)
Anthropic·Anthropic Academy
Free

Introduction to Model Context Protocol

Teaches the MCP architecture and how to build servers with the Python SDK, exposing tools, resources, and prompts, then testing them with the MCP Inspector. For Python developers who want to connect Claude (or any MCP client) to their own data and services the standard way.

intermediate Self-paced Certificate
shareAI-lab·GitHub
Free

Learn Claude Code -- Harness Engineering for Real Agents

A 0-to-1 course that rebuilds a Claude Code-style coding agent one mechanism per lesson (tool use, permissions, hooks, planning, subagents, context compaction, memory, task systems, scheduling, agent teams, MCP plugins and a goal loop) with runnable Python and diagrams. It suits developers who use coding agents daily and want to understand, or build, the harness around the model.

intermediate 17 progressive lessons, self-paced
Hugging Face and Anthropic·Hugging Face
Free

Model Context Protocol (MCP) Course

Built by Hugging Face in partnership with Anthropic, it covers MCP architecture and core concepts, then an end-to-end use case and a deployed use case, plus bonus units, with tools such as Gradio. For developers who want a free, hands-on MCP course with free certificates to complement Anthropic's own MCP courses.

intermediate 4 units plus bonus; ~3-4 hours per week, about a week per unit Certificate
Microsoft·GitHub
Free

Model Context Protocol (MCP) Curriculum for Beginners

A 13-module curriculum on MCP fundamentals, security, building servers and clients, VS Code integration, testing, deployment, and advanced topics like OAuth2 and scaling, with samples in C#, Java, JavaScript, Python, Rust, and TypeScript. For developers in any language who want a thorough free grounding in MCP.

beginner 13 modules, self-paced
Anthropic·Anthropic Academy
Free

Model Context Protocol: Advanced Topics

Goes beyond MCP basics into sampling, log and progress notifications, roots-based file access control, JSON message types, and the STDIO and StreamableHTTP transports, including state handling for production servers. For developers who finished Introduction to Model Context Protocol and now need to ship MCP servers and clients to production.

advanced 15 lectures, ~1 hour of video, 2 quizzes Certificate

Coding with AI

Build real software by working with AI coding agents, even if you are new to code.

All Coding with AI
DataTalks.Club (Alexey Grigorev and Bhavani Ravi)·GitHub
Free

AI Dev Tools Zoomcamp: AI-Native Software Engineering

A free community course on building and shipping software with AI coding agents: spec-driven workflows with AGENTS.md, an AI-assisted full-stack app, testing and containerized deployment, observability, and agent building blocks like SKILL.md skills, subagents and parallel Git worktrees. It suits working developers who want an engineering-grade, project-based alternative to vibe-coding tutorials, with an optional cohort for accountability.

intermediate 5 modules; 2026 cohort started 2026-08-31, self-paced anytime Certificate
Anthropic·Anthropic Academy
Free

Claude Code 101

Anthropic's own introduction to Claude Code, from installation and a first prompt through the explore-plan-code-commit workflow, context management, code review, and customizing with CLAUDE.md, subagents, skills, MCP and hooks. Start here if you are new to AI coding agents (or new to software engineering) and want the vendor's recommended daily workflow before moving on to Claude Code in Action.

beginner 12 lectures, ~1.5 hours of video, 1 quiz Certificate
ExamPro (Andrew Brown), published by freeCodeCamp.org·freeCodeCamp
Free

Claude Code Essentials

A feature-by-feature tour of Claude Code covering the agent loop, sessions, permission modes, sandboxing, hooks, headless runs, IDE and GitHub Actions integrations, CLAUDE.md memory, agent skills, MCP and multi-agent sub-agents. It suits developers who already use Claude Code casually and want one complete, structured reference instead of scattered short clips.

intermediate ~12 hours (single video)
Stanford University (Mihail Eric and teaching team)·Stanford University
Free

CS146S: The Modern Software Developer

Stanford's course on AI-assisted software development with coding agents, covering MCP, agent skills, spec-driven development, loop engineering and the 'software factory', with hands-on assignments in a public GitHub repo and practitioner guest talks. It suits developers who want a university-designed syllabus for working alongside coding agents and can follow along from slides and assignments rather than video.

intermediate One academic quarter (Fall 2026: Sep 22 - Dec 3)
OpenAI·OpenAI Academy
Free

Extend Codex Workflows

Turns individual Codex habits into team practice: shared guidance placed where Codex can use it, reusable Codex skills, visible review evidence, and clear ownership across parallel or long-running work. For developers and tech leads already using Codex who want practices the whole team can follow and review.

intermediate ~90 minutes (lessons plus guided lab) Certificate
OpenAI·OpenAI Academy
Free

Get Started with Codex

Learn to use OpenAI Codex for well-scoped engineering work in a real repository: giving it the right context, defining completion criteria, verifying changes, and producing evidence a reviewer can check. For working developers with no Codex experience who are comfortable with shells, tests, pull requests and diffs.

intermediate ~80 minutes (lessons plus guided lab) Certificate
Microsoft and GitHub·Microsoft Learn
Free

GitHub Copilot Fundamentals Part 1 of 2

The official introduction to GitHub Copilot: responsible use, prompt engineering, Copilot Spaces, advanced features, Copilot in the IDE, chat, GitHub.com and the command line, plan management and customization, and generating unit tests. For developers and admins new to Copilot who want the free vendor path before Part 2 or the GitHub Copilot certification.

beginner 9 modules, ~5 hours 15 minutes
Anthropic·Anthropic Academy
Free

Introduction to agent skills

Teaches how to build, configure and share Skills in Claude Code, the reusable markdown instructions Claude applies automatically to matching tasks, including multi-file skills, how skills differ from other Claude Code features, and troubleshooting. Take it if you already use Claude Code and want to package your team's conventions into skills that load on demand.

intermediate 6 lessons, self-paced
Anthropic·Anthropic Academy
Free

Introduction to subagents

Covers how subagents work in Claude Code, creating custom ones with the /agents command, designing them with structured output, obstacle reporting and limited tool access, and the anti-patterns to avoid. For Claude Code users running longer sessions who want to delegate work and keep the main context window clean.

intermediate 4 lessons, self-paced
Microsoft and GitHub·Microsoft Learn
Free

Perform code maintenance tasks using GitHub Copilot Agent

Hands-on modules using Copilot's agent mode to consolidate duplicate logic, refactor large functions, simplify conditionals, implement code improvements, and remediate GitHub issues and secret scanning alerts. For developers with a year or more of experience who want practice using a coding agent on real maintenance and security work.

intermediate 6 modules, ~8 hours
OpenAI·OpenAI Academy
Free

Scale Codex Across Teams and Systems

Covers coordinating Codex across complex engineering changes: splitting work into verifiable workstreams, writing verification contracts that define the evidence each must produce, and bringing parallel outputs back together safely. For experienced developers, platform engineers and tech leads running Codex on large repositories with governance requirements.

advanced ~100 minutes (lessons plus guided lab) Certificate

AI Automation & No-Code

Wire AI into your daily work and business with no-code automation and agents.

All AI Automation & No-Code
OpenAI·OpenAI Academy
Free

Agents and Workflows

Teaches how to direct ChatGPT agents through structured work: providing context, defining outputs, setting boundaries, reviewing results and improving workflows over time. The third step in OpenAI's Apply AI at Work track, for knowledge workers comfortable with AI who want to delegate multi-step tasks to agents.

intermediate ~90 minutes Certificate
Zapier Academy·Zapier
Free

AI Builder Path

Zapier's official no-code path from platform orientation and basic Zaps (triggers, actions, field mapping, building with Copilot) to intermediate Zaps using AI by Zapier's agentic steps, tools and approval gates alongside Formatter, Search and Paths. It suits non-technical staff who want to build reliable AI workflows for their own work, and it anchors Zapier's 2026 '1 Million AIs' free AI-education pledge.

beginner ~2 hours (3 courses, 23 lessons) Certificate
Make Academy·Make
Free

Automation to AI Agents: Foundation

Make's official learning path from AI fundamentals and LLMs to using AI inside Make scenarios and building AI agents in Make, ending in an assessment for a shareable badge (an Advanced path follows for agent builders). It suits operations and marketing people new to Make who want to understand when to use plain automation versus an AI agent.

beginner 6 courses + 1 assessment, ~2-3.5 hours Certificate
Microsoft·Microsoft Learn
Free

Create agents in Microsoft Copilot Studio

Microsoft's low-code path for building custom agents in Copilot Studio: getting started with the agent harnesses, designing conversations with topics, grounding answers in knowledge sources with generative AI, and adding structured automation through workflow tools. For makers and functional consultants automating business processes in Microsoft 365 without heavy coding.

intermediate 4 modules, ~3.7 hours
Anthropic·Anthropic Academy
Free

Introduction to Claude Cowork

Shows how to hand Claude real multi-step work on your own files and projects: the Cowork task loop, standing context, skills, plugins, Claude in Chrome and Claude for Microsoft 365, and safe sharing practices. Aimed at non-developers who want agent-style automation of everyday knowledge work without writing code.

beginner 14 lectures, ~30 minutes of video, 1 quiz Certificate
n8n Academy·n8n
Free

n8n Foundations (N8N101 Essentials, N8N102 Integrations, N8N103 In Practice: AI, Testing & Best Practices)

n8n's official academy, launched June 2026, with three graded courses: building first workflows and data mapping, calling APIs and connecting apps, and then AI agents with tools and memory alongside testing, error handling and production practices. It suits anyone starting with n8n who wants the vendor's own structured path, with hands-on graded exercises and a badge, before following YouTube creators.

beginner 3 courses, ~2-4 hours each Certificate

Machine Learning

Supervised and unsupervised learning, model evaluation, and the math behind it.

All Machine Learning
Kaggle
Free

Intro to Machine Learning

A micro-course that gets you from zero to your first random forest model and Kaggle competition submission in an afternoon. Perfect for people who learn by doing and want immediate, runnable code.

beginner ~3 hours (7 lessons) Certificate
MIT·MIT OpenCourseWare
Free

Introduction to Machine Learning (6.036)

MIT's undergraduate ML course (Fall 2020) with notes, auto-graded exercises, and labs covering perceptrons, gradient descent, neural nets, CNNs, RNNs, and reinforcement learning. Best for learners comfortable with linear algebra who want an MIT-level problem-set experience for free.

intermediate 13 weeks (one semester)
Caltech
Free

Learning From Data

Yaser Abu-Mostafa's celebrated course explains why learning works: VC dimension, bias-variance, overfitting, regularization, and validation, alongside core algorithms. Take it if you want the theoretical intuition that most applied courses skip.

intermediate 18 lectures plus homework
Google
Free

Machine Learning Crash Course

Google's refreshed crash course mixes short videos, interactive visualizations, and quizzes across linear and logistic regression, data handling, neural networks, embeddings, LLMs, and production ML. Ideal for engineers who want a practical, fast overview before committing to a longer program.

beginner ~15 hours (12 modules)
Microsoft·GitHub
Free

Machine Learning for Beginners - A Curriculum

Microsoft Cloud Advocates' open curriculum walks through regression, classification, clustering, NLP, time series, and RL with Scikit-learn, using real-world datasets from around the globe. A great structured syllabus for self-learners and study groups who prefer notebooks over videos.

beginner 12 weeks, 26 lessons
Stanford University·YouTube
Free

Stanford CS229: Machine Learning led by Andrew Ng | Autumn 2018

The complete recorded lectures of Stanford's graduate ML course, deriving generalized linear models, SVMs, kernels, EM, learning theory, and RL from first principles. Choose this if you want the mathematical depth behind the algorithms, not just how to call them.

advanced 20 lectures, ~1.5 hours each

Deep Learning

Neural networks, CNNs, RNNs, transformers, PyTorch and TensorFlow.

All Deep Learning
d2l.ai (Zhang, Lipton, Li & Smola)·d2l.ai
Free

Dive into Deep Learning

An interactive, code-first textbook with every concept implemented in PyTorch, NumPy/MXNet, JAX, and TensorFlow, from linear regression through transformers and optimization. Best for learners who want a rigorous reference that doubles as a hands-on course.

intermediate Self-paced (full textbook)
MIT·MIT OpenCourseWare
Free

MIT 6.S191: Introduction to Deep Learning

MIT's fast-moving bootcamp updates each year to cover sequence modeling, vision, generative models, RL, and LLMs, with TensorFlow/PyTorch labs including LLM fine-tuning. Great for getting current on the deep learning landscape in a compact format.

intermediate 9 lectures plus 3 software labs (~2 weeks intensive)
3Blue1Brown (Grant Sanderson)·YouTube
Free

Neural networks

Grant Sanderson's animated series builds visual intuition for what neural networks compute, how gradient descent and backpropagation work, and how transformers and attention process text. Watch it before or alongside any formal course to make the math click.

beginner ~3 hours total (8 videos)
NYU Center for Data Science·GitHub
Free

NYU Deep Learning (DS-GA 1008), Spring 2021

Yann LeCun's lectures paired with Alfredo Canziani's PyTorch practica cover energy-based models, self-supervised learning, graph networks, and more, with notebooks and multilingual notes. For learners who want a research-oriented perspective straight from a founder of the field.

advanced 15 weeks of lectures and practica
fast.ai
Free

Practical Deep Learning for Coders

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.

intermediate 9 lessons, ~90 minutes each plus notebooks

Natural Language Processing

Text processing, embeddings, sequence models, and modern transformer NLP.

All Natural Language Processing
Stanford University
Free

CS224N: Natural Language Processing with Deep Learning

Stanford's flagship NLP course moves from word vectors and RNNs to transformers, pretraining, RLHF, and modern LLM topics with public slides and assignments. The go-to self-study syllabus for anyone who wants to understand how today's language models actually work.

advanced 10 weeks (one quarter)

Computer Vision

Image classification, object detection, segmentation, and generative image models.

All Computer Vision
Kaggle
Free

Computer Vision

Build an image classifier with convolutional networks and transfer learning in Keras, with notebooks you run in the browser. A compact starting point for Kaggle users who want to enter their first vision competition.

intermediate ~4 hours (6 lessons) Certificate
Stanford University
Free

CS231n: Deep Learning for Computer Vision

The definitive computer vision deep learning course, with public notes and assignments on CNNs, training tricks, detection, segmentation, generative models, and vision transformers. Self-study it when you want to build vision systems from scratch rather than only call APIs.

advanced 10 weeks (one quarter)

Reinforcement Learning & Robotics

Markov decision processes, policy gradients, deep RL, and robotics applications.

All Reinforcement Learning & Robotics
Stanford University
Free

CS234: Reinforcement Learning

Emma Brunskill's course covers tabular RL, deep Q-learning, policy gradients, exploration, offline RL, and RLHF with public lecture slides and assignments. A strong theory-plus-practice sequel to David Silver's lectures.

advanced 10 weeks (one quarter)
UC Berkeley
Free

Deep Reinforcement Learning (CS 285)

Sergey Levine's graduate course goes deep on policy gradients, actor-critic, model-based RL, offline RL, exploration, and inverse RL with PyTorch homework. For learners aiming at RL research or robotics who want the most advanced free syllabus available.

advanced One semester (~25 lectures)
Hugging Face
Free

Deep Reinforcement Learning Course

Train agents from Q-learning to PPO and multi-agent setups in Colab, publish them to the Hub, and compete on leaderboards. Ideal for learners who want deep RL to be practical and fun from the first unit, with a free certificate at the end.

intermediate 8 units plus bonus units, self-paced Certificate
UCL / Google DeepMind (David Silver)·UCL / Google DeepMind
Free

Reinforcement Learning (UCL Advanced Topics 2015, COMPM050/COMPGI13)

David Silver's classic lectures cover MDPs, dynamic programming, Monte Carlo and TD learning, function approximation, policy gradients, and planning, closely tracking the Sutton and Barto textbook. Still the standard first RL course for anyone serious about the field.

intermediate 10 lectures, ~1.5 hours each
OpenAI·OpenAI Academy
Free

Spinning Up in Deep RL

OpenAI's educational package pairs a concise introduction to RL theory with clean reference implementations of VPG, TRPO, PPO, DDPG, TD3, and SAC, plus a curated key-papers list and exercises. Use it to bridge the gap between lecture understanding and writing your own deep RL code.

intermediate Self-paced (docs, exercises, and code)

Data Science & Math for AI

Linear algebra, statistics, calculus, Python, and data analysis for AI work.

All Data Science & Math for AI
Khan Academy
Free

Linear algebra

Sal Khan's patient video walkthroughs of vectors, span, null and column spaces, linear transformations, inverses, determinants, orthogonality, and eigenvectors. The place to start if you need linear algebra from scratch before any ML math course.

beginner Self-paced (3 units: vectors and spaces, matrix transformations, alternate coordinate systems)
MIT·MIT OpenCourseWare
Free

Linear Algebra (18.06)

Gilbert Strang's legendary lectures on the four fundamental subspaces, projections, determinants, eigenvalues, and the SVD, with solved problem sets and exams. The gold standard for building the linear algebra intuition that underlies all of ML.

intermediate 35 lectures plus problem sets and exams
StatQuest (Josh Starmer, PhD)·YouTube
Free

StatQuest with Josh Starmer

Clearly explained, song-punctuated videos on statistics fundamentals, regression, cross-validation, trees and boosting, PCA, and neural networks through transformers. The best quick-reference when a concept in another course does not click.

beginner Hundreds of 5-25 minute videos, self-paced

MLOps & AI Engineering

Deployment, monitoring, data pipelines, and engineering practices for real AI systems.

All MLOps & AI Engineering
Stanford University (Chip Huyen)·GitHub
Free

CS 329S: Machine Learning Systems Design

Chip Huyen's course notes and slides on designing reliable, scalable ML systems: data engineering, feature stores, training infrastructure, deployment, monitoring, and continual learning, later expanded into her O'Reilly book. Read it to think like an ML systems designer rather than a model trainer.

advanced 10 weeks of slides and notes
Databricks·Databricks Academy
Free

Databricks Academy Self-Paced Training: Machine Learning Engineer Path

Databricks' free role-based path takes you from getting started with ML on the platform through data preparation, model development, deployment, and MLOps with MLflow. Useful for engineers whose employers run on Databricks or who want badge-backed lakehouse MLOps skills.

beginner ~12 hours Certificate
Full Stack Deep Learning
Free

Full Stack Deep Learning - 2022 Course

Covers the full lifecycle of a deep learning product: infrastructure and tooling, troubleshooting, data management, deployment, monitoring, and ethics, with labs building a text recognizer app. Ideal for ML engineers who can train a model but need to ship one.

intermediate 9 lectures plus labs (~12 weeks)
Decoding ML (Decoding AI)·GitHub
Free

LLM Twin Course: Building Your Production-Ready AI Replica

An end-to-end LLMOps build pairing written lessons with code: data crawling and change-data-capture, a streaming feature pipeline with advanced RAG, instruction-dataset generation, fine-tuning and evaluation, and a deployed RAG inference service with prompt monitoring. It suits ML and backend engineers who want to see every production component of an LLM system, not just the prompt.

intermediate 12 lessons (10 core + 2 bonus), self-paced
Anyscale (Goku Mohandas)·Made With ML
Free

Made With ML

Goku Mohandas's lesson series walks through designing, developing, deploying, and iterating on a production ML application with experiment tracking, testing, versioning, serving, CI/CD, and monitoring. One of the clearest end-to-end MLOps walkthroughs for engineers moving from notebooks to production.

intermediate Self-paced (foundations + MLOps lessons)

AI for Business & Leadership

Executive education and strategy courses for leaders deploying AI.

All AI for Business & Leadership
Microsoft·Microsoft Learn
Free

Transform your business with AI

A free Microsoft Learn path for business leaders covering how to leverage AI tools, create business value, embrace responsible AI principles and scale AI across an organization. Useful for managers planning Azure or Copilot-based AI adoption who want a vendor's structured playbook at no cost.

beginner 4 modules, approx. 3-4 hours

AI Ethics, Safety & Policy

Fairness, alignment, governance, and the societal impact of AI.

All AI Ethics, Safety & Policy
BlueDot Impact
Free

AI Alignment

The leading structured course on AI alignment, combining curated readings with weekly facilitated small-group discussions and a capstone project. Aimed at engineers, researchers and policy people who want to move into AI safety work.

intermediate 12 weeks, approx. 5 hrs/week (8 weeks learning plus 4-week project) Certificate
Microsoft·Microsoft Learn
Free

Embrace responsible AI principles and practices

A free Microsoft Learn module on the six responsible AI principles (fairness, reliability and safety, privacy and security, inclusiveness, transparency, accountability) and how to turn them into governance systems. Useful for business leaders and compliance teams building an AI governance policy.

beginner 9 units, approx. 51 minutes
University of Helsinki
Free

Ethics of AI

A free, text-based University of Helsinki course on non-maleficence, accountability, transparency, human rights and fairness in AI, built with the cities of Helsinki, Amsterdam and London. Ideal for policymakers, public servants and anyone who wants a rigorous but non-technical grounding in AI ethics.

beginner 7 chapters, self-paced (approx. 20 hours) Certificate
UNESCO with LG AI Research·Coursera
Free

Global MOOC on the Ethics of AI

UNESCO's first Coursera course, built on its 2021 Recommendation on the Ethics of AI, covers human-AI interaction, safety, fairness, privacy, transparency, sustainability and global AI governance. Best for professionals and policymakers who want the internationally agreed ethics framework straight from the source.

intermediate 10 modules, approx. 10 hours Certificate
Center for AI Safety
Free

Intro to ML Safety

Dan Hendrycks' technical course on safety engineering, adversarial robustness, anomaly detection, trojans, machine ethics and systemic AI risk, with coding assignments. For ML practitioners and graduate students who want hands-on exposure to empirical AI safety research.

advanced Approx. 8 weeks of lectures and assignments, self-paced
Center for AI Safety·Coursera
Free

Introduction to AI Safety

A free, non-technical abridgement of the 'AI Safety, Ethics, and Society' textbook covering what AI can do today, the major risks from AI and governance strategies. A good first stop for policymakers, journalists and students before committing to a longer safety course.

beginner Approx. 4 hours, 3 modules