Best AI & machine learning Courses
Hand-picked AI and tech courses, free and paid, that are worth your time.
67 courses · page 1 of 2
Building Systems with the ChatGPT API
Shows how to chain several LLM calls into a working customer-service style system, covering classification, moderation, chain-of-thought and output evaluation. Suits Python developers moving past single prompts.
View courseLangChain for LLM Application Development
An introduction to the LangChain framework: models, prompts, memory, chains, question answering over documents and simple agents. Useful for developers who want to build LLM apps quickly in Python.
View courseLangChain Chat with Your Data
Build a chatbot that answers questions from your own PDFs and web pages using document loading, splitting, embeddings, vector stores and retrieval. A solid first step into retrieval augmented generation.
View courseBuilding Generative AI Applications with Gradio
Create quick web demos for text summarisation, image captioning, image generation and chat using Gradio and open models. Handy for anyone who wants to showcase AI projects in a portfolio.
View courseLarge Language Models with Semantic Search
Learn how embeddings, dense retrieval and reranking improve keyword search, and how to combine search results with an LLM to answer questions. Suits developers building search or RAG features.
View courseBuilding and Evaluating Advanced RAG
Learn advanced retrieval methods such as sentence-window and auto-merging retrieval, and how to measure RAG quality with evaluation metrics. Useful for teams putting document question answering into production.
View courseMulti AI Agent Systems with crewAI
Design teams of role-based AI agents that collaborate on business tasks like research, customer support and content planning using the open-source crewAI framework. Beginner friendly for Python users.
View courseBuilding Agentic RAG with LlamaIndex
Build a research agent that routes queries, calls tools and reasons over multiple documents with LlamaIndex. A compact course for developers who want smarter document assistants.
View courseQuantization Fundamentals with Hugging Face
Learn how to shrink models with linear quantization and lower-precision data types so they run on smaller hardware, using Hugging Face tools. Suits learners curious about efficient model deployment.
View courseOpen Source Models with Hugging Face
Find and use open models from the Hugging Face Hub for text, audio, image and multimodal tasks, then share demos with Gradio and Spaces. Great for beginners building quick AI prototypes.
View courseBuilding toward Computer Use with Anthropic
Work through the Claude API features behind computer use: multimodal prompts, tool use, prompt caching and an agent that controls a desktop. Good for developers exploring AI agents.
View courseAttention in Transformers: Concepts and Code in PyTorch
Understand the attention mechanism behind transformers and code self-attention, masked attention and multi-head attention in PyTorch. Good for learners who want to see how LLMs work inside.
View courseHow Transformer LLMs Work
A visual walk through tokenizers, embeddings, attention and the transformer block, explaining how modern language models generate text. Suits anyone who wants a clear mental model of LLMs.
View courseEvaluating AI Agents
Learn to trace, test and score AI agents, measuring each step such as routing and tool calls so you can improve reliability systematically. Useful for developers shipping agent-based products.
View courseGetting Started with Mistral
Explore Mistral's open and commercial models, using them for prompting, function calling, JSON output and RAG through the API. A quick start for developers comparing LLM providers.
View courseEmbedding Models: from Architecture to Implementation
Learn how embedding models evolved from word vectors to transformer-based encoders and how to train a dual encoder for semantic search. Good background for anyone building retrieval systems.
View courseIntroduction to on-device AI
Learn how to optimise and deploy AI models on phones and edge devices, covering model conversion, quantization and on-device testing. Suits developers interested in mobile and embedded AI.
View courseHugging Face Machine Learning for Games Course
See how AI tools can be used in game development, for example to create NPCs and game assets, with practical demos. A good fit for game developers and hobbyists curious about ML.
View coursePractical Data Ethics
Covers ethical issues in data science and AI such as disinformation, bias, privacy, surveillance and algorithmic accountability, with readings and lectures. Useful for anyone building or deploying data products.
View courseIntro to Machine Learning
Build your first machine learning models, learning about decision trees, random forests, validation and overfitting using real datasets. Suits beginners who know a little Python.
View courseIntro to Game AI and Reinforcement Learning
Build game-playing agents, starting with simple heuristics and minimax search and moving on to reinforcement learning. A fun entry point for learners curious about how AI plays games.
View courseIntro to AI Ethics
Explore practical tools for building fairer, more responsible AI, including human-centred design, identifying bias, fairness metrics and model cards. Useful for anyone who builds or manages AI systems.
View courseElements of AI
A friendly, non-technical introduction to what AI is, what it can and cannot do, and how it affects society, with no maths or coding required. Ideal for students and professionals from any field.
View courseEthics of AI
Examines the ethical questions raised by AI, including fairness, transparency, accountability, privacy and human rights, using real examples. Suits anyone who wants to think critically about responsible AI use.
View courseAI Fluency: Framework & Foundations
Learn a practical framework for working with AI effectively and responsibly, covering delegation, clear description, critical evaluation and diligence. Useful for professionals in any role.
View courseAI Fluency for educators
Helps teachers and faculty apply AI fluency ideas to lesson planning, course design and their own teaching practice in a thoughtful way. Suited to educators at schools and universities.
View courseAI Fluency for students
Shows students how to use AI to support learning, career planning and academic work while keeping their own thinking and integrity. Ideal for university and college students.
View courseTeaching AI Fluency
Guides educators in teaching and assessing AI fluency with their students, with ready-to-adapt ideas for classroom activities. Useful for teachers designing AI literacy lessons.
View courseIntroduction to agent skills
Learn what agent skills are and how to create, organise and share them so Claude can follow repeatable workflows. Good for developers and power users customising AI tools.
View courseAI Capabilities and Limitations
Explains what current AI models do well, where they fall short and why, so you can decide when to trust their output. Useful for anyone using AI tools at work or study.
View courseMachine Learning Specialization
Andrew Ng's beginner-friendly three-course series on regression, classification, neural networks, decision trees, recommender systems and reinforcement learning using Python. Ideal first step for aspiring ML engineers.
View courseAI Fluency
A friendly starting point for anyone new to AI: understand what today's AI tools can do, how to use them responsibly at work, and how to get useful results from chat assistants.
View courseAI concepts for developers and technology professionals
Covers the core ideas behind machine learning, generative AI, computer vision and language models, giving developers and IT learners the vocabulary needed before building AI solutions on Azure.
View courseGet started with AI applications and agents on Azure
Hands-on introduction to building AI apps and simple agents with Azure services, suited to students and junior developers who want practical experience beyond theory.
View courseIntroduction to AI literacy
Builds everyday AI literacy: how AI systems work, where they fail, and how to judge their output critically. Good for students, teachers and non-technical job seekers.
View courseGitHub Copilot Fundamentals Part 1 of 2
Shows how to use GitHub Copilot as an AI pair programmer in your editor, write effective prompts for code, and apply it responsibly. Aimed at students and working developers.
View courseIntroduction to Generative AI
A short microlearning course explaining what generative AI is, how it differs from traditional machine learning, and which Google tools support it. Ideal first step for complete beginners.
View courseIntroduction to Large Language Models
Learn what large language models are, where they are used, and how prompt tuning improves their output. A quick, beginner-friendly overview for students and professionals.
View courseIntroduction to Image Generation
Explains how diffusion models create images from noise and how they are trained and deployed on Google Cloud. Good for learners curious about AI image tools.
View courseResponsible AI: Applying AI Principles with Google Cloud
Explore how organisations put responsible AI principles into practice, with real examples of balancing innovation, fairness and risk. Suits managers, students and AI practitioners.
View courseGen AI: Beyond the Chatbot
First course of Google's Gen AI Leader path: see how generative AI goes beyond chat to transform business work, with no technical background required.
View courseGen AI: Unlock Foundational Concepts
Learn the key ideas behind generative AI, including data, models and machine learning approaches, in plain business language. Second course in the Gen AI Leader path.
View courseGen AI: Navigate the Landscape
Map out the generative AI ecosystem, from infrastructure and models to platforms and agents, and how organisations choose among them. Third course of the Gen AI Leader path.
View courseGen AI Apps: Transform Your Work
Discover Google's generative AI apps such as Gemini for Workspace and learn practical prompting techniques to speed up everyday work. Fourth course in the Gen AI Leader path.
View courseGen AI Agents: Transform Your Organization
Understand AI agents, how they automate business processes, and how organisations can adopt them responsibly. Final course of Google's Gen AI Leader learning path.
View courseInnovating with Google Cloud Artificial Intelligence
Business-level introduction to AI and machine learning on Google Cloud, including how to pick the right AI solution for a problem. Part of Cloud Digital Leader preparation.
View courseMachine Learning Crash Course
Google's well-known self-paced ML course with videos, visualisations and exercises covering regression, classification, neural networks and LLMs. Great for students and developers starting machine learning.
View courseIntroduction to Machine Learning
A brief, non-mathematical overview of what machine learning is, the main model types and how they learn. Good preparation before tackling the Machine Learning Crash Course.
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