Generative AI, large language models, agents and applied AI for both builders and business users.
Explore generative AI with Andrew Ng, covering practical prompting, AI project decisions, workplace applications, and responsible use.
Learn to use Microsoft Copilot across Word, Excel, PowerPoint, Teams, and Outlook, with practical guidance on prompting and data protection.
Build an MIT machine learning and AI certificate through two core courses and selected electives, with at least 16 qualifying study days.
A University of Pennsylvania course on AI business strategy, responsible governance, bias, and explainable AI in one flexible week.
Learn PyTorch fundamentals through hands-on exercises covering neural networks, training loops, classification, regression, and model evaluation.
Five-course sequence from DeepLearning.AI covering neural networks, CNNs, RNNs and transformers, taught by Andrew Ng with Python and TensorFlow.
A hands-on DataCamp course where you build LangChain agents, define custom tools, and create LangGraph chatbots using ReAct reasoning.
A hands-on Udemy course taking learners from Python basics to building production-ready AI agents with LangChain, LangGraph, and CrewAI.
A short, hands-on course teaching intermediate Python learners to build controllable AI agents using LangChain's LangGraph framework.
A 1h35m beginner short course on building multi-agent systems with AutoGen, covering reflection, tool use, planning, and collaboration.
A free, under-two-hour beginner course on prompt engineering with ChatGPT: core techniques, debugging prompts, real use cases, enterprise security.
A beginner-friendly DataCamp course that teaches practical ChatGPT prompt engineering skills you can apply to real work right away.
A free DeepLearning.AI short course teaching developers to write effective prompts and build simple applications on the OpenAI API using.
A Vanderbilt University specialization teaching prompt engineering techniques to effectively work with ChatGPT and other generative AI tools.
A hands-on DataCamp course on building chatbots and RAG pipelines using LangChain, covering chains, agents, and retrieval tools in depth.
Code-along Python course on building LLM apps with LangChain, Pinecone, OpenAI and Gemini, finishing with a document Q&A app and a summarizer.
A seven-course IBM program on Coursera covering LLM fundamentals, fine-tuning, RAG and LangChain, ending with a hands-on question-answering bot.
A hands-on course covering how LLMs are built, fine-tuned, and deployed, taught by AWS AI practitioners through DeepLearning.AI on Coursera.
A 3-course Coursera specialization teaching non-technical marketers to use, apply, and build generative AI tools for real campaigns.
A three-course specialization helping HR professionals apply generative AI tools to recruitment, onboarding, and workforce planning tasks.
A no-code Nanodegree teaching business leaders to question, direct, and judge AI-driven data science work.
A four-course specialization teaching business leaders to apply ChatGPT, Gemini, DeepSeek, and Copilot to real marketing and project work.
Beginner-friendly IBM specialization teaching AI basics, generative AI, prompt engineering, and no-code chatbot building for anyone.
Andrew Ng's foundational, non-technical introduction to AI concepts and business strategy, recommended as a first step for beginners.
Learn to leverage generative AI to automate tasks, boost productivity, and unlock your creative potential with leading industry experts.
Master advanced prompting and Python to build, orchestrate, and deploy intelligent multi-agent AI systems that solve real-world problems.
Master generative AI and build intelligent applications by learning prompt engineering, LangChain, and model fine-tuning in this hands-on path.
Master Microsoft 365 Copilot and Azure AI to boost workplace productivity, streamline workflows, and drive business innovation without writing code.
Artificial Intelligence is the fastest-moving category on this site, and it now splits into two audiences. One wants to build: large language model applications, retrieval pipelines, fine-tuning, autonomous agents, and the deep learning that underpins language and vision systems. The other wants to apply, using ChatGPT, Copilot, Gemini and Claude to do existing work faster without writing code. Both are covered here, kept in separate subcategories so a business user is not pushed into a PyTorch course and an engineer is not sold prompt basics. Governance and safety material sits alongside, since deployment increasingly depends on it.
