Learn from the source, for free.
Courses from Stanford, MIT, OpenAI, Anthropic, NVIDIA, Google, and more — curated for working professionals who need to level up fast.
32 courses found
CS50's Introduction to AI with Python
Harvard's popular course on AI concepts and algorithms — search, knowledge, uncertainty, optimization, learning, and neural networks.
Agentic AI
Andrew Ng's course on agentic AI design patterns — reflection, tool use, planning, and multi-agent collaboration using raw Python.
Deep Learning Specialization
Andrew Ng's foundational 5-course specialization on deep learning — neural networks, CNNs, RNNs, and sequence models.
Generative AI for Everyone
Andrew Ng's course on understanding generative AI — what it is, how it works, and how to apply it in your work and life.
AI Agents for Beginners
12 lessons covering the fundamentals of building AI agents — from simple conversational bots to complex multi-agent systems.
AI for Beginners
12-week, 24-lesson curriculum covering AI fundamentals with practical lessons, quizzes, and labs using TensorFlow and PyTorch.
Generative AI for Beginners
21-lesson comprehensive course by Microsoft Cloud Advocates to learn the fundamentals of building generative AI applications.
AI Research Foundations (DeepMind)
Google DeepMind curriculum on AI technologies behind Gemini — build and fine-tune modern language models from the ground up.
Generative AI Learning Path
Comprehensive learning path covering LLMs, prompt engineering, and hands-on AI development in Google Cloud.
Introduction to Generative AI
Overview of generative AI concepts — from the fundamentals of large language models to responsible AI principles.
Fundamentals of Deep Learning
Learn the fundamentals of deep learning with hands-on exercises using NVIDIA GPUs in the cloud. Covers training and deployment.
Building RAG Agents with LLMs
Hands-on course on building retrieval-augmented generation agents using LLMs, with GPU-accelerated labs.
Generative AI Explained
No-code introduction to generative AI concepts — understand LLMs, diffusion models, and the generative AI landscape.
How to AI (Almost) Anything
Learn to apply modern AI and foundation models to novel real-world data modalities, with principles of multimodal AI.
6.S191: Introduction to Deep Learning
MIT's official introductory course on deep learning — covers neural networks, CNNs, RNNs, transformers, and generative models.
6.034: Artificial Intelligence
Foundational MIT course on AI covering knowledge representation, problem solving, and learning methods.
AI 101
MIT's introduction to artificial intelligence designed for those with little to no background in the subject.
CS231n: Deep Learning for Computer Vision
Deep dive into convolutional neural networks and their applications to image recognition, detection, and generation.
Machine Learning Specialization
Beginner-friendly specialization by Andrew Ng and DeepLearning.AI covering regression, neural networks, decision trees, and recommender systems.
CS221: Introduction to AI
Principles and techniques of artificial intelligence — search, logic, machine learning, and applications to real-world problems.
CS229: Machine Learning
Stanford's flagship ML course covering supervised/unsupervised learning, learning theory, reinforcement learning, and control.
Introduction to GPTs
Learn how to create, customize, and publish your own GPTs — tailored versions of ChatGPT for specific tasks.
Deep Research
Explore how to use ChatGPT's Deep Research feature for comprehensive, multi-source research and analysis.
ChatGPT for Data Analysis
Learn to use ChatGPT as a powerful data analysis tool — upload datasets, generate visualizations, and extract insights.
Advanced Prompt Engineering
Master advanced prompting techniques to get better, more consistent results from ChatGPT and OpenAI models.
OpenAI LLMs and ChatGPT
Understand how large language models work, what ChatGPT can do, and how to get the most out of OpenAI tools.
Model Context Protocol: Advanced Topics
Build MCP servers and clients from scratch using Python. Master tools, resources, and prompts primitives to connect Claude with external services.
Introduction to Model Context Protocol
Learn the fundamentals of MCP — the open protocol for connecting AI models to external tools, resources, and data sources.
Building with the Claude API
The largest course on the platform: 84 lectures and 8+ hours covering everything you need to integrate Claude into production applications.
Claude Code 101
Get started with Claude Code — learn how to use Claude as an AI coding assistant for writing, debugging, and understanding code.
AI Fluency: Framework & Foundations
Build core AI literacy with a structured framework for understanding, evaluating, and collaborating with AI systems responsibly.
Claude 101
Learn the fundamentals of Claude — how to use it for everyday work tasks, understand core features, and explore resources for advanced learning.