The best free AI courses for every level in 2026

An excellent general overview of Generative AI technology, suitable for all audiences. The three-hour course covers what gen AI can and can’t do, an overview of AI tools, and the future impact of generative AI on society.

This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers the Google tools available to help you develop your own Gen AI apps.

Generative AI expert Pinar Seyhan Demirdag covers the basics of generative AI, with topics including what it is, how it works, how to create your own content, different types of models, future predictions, and ethical implications.

This introductory-level microlearning course explains what responsible AI is, why it’s important, and how Google implements responsible AI in their products. It also introduces Google’s 3 AI principles.

Learn the skills to craft compelling prompts that yield better, more accurate responses. From understanding contextual cues to mitigating biases, the course aims to provide learners with the skills and techniques to effectively interact with AI systems.

Consisting of three one-hour modules, this well-rounded course provides an introduction to the concepts of AI in an informal and engaging way. A great course to watch in your lunch hour over a few days and learn about the technology behind machine learning, computer vision, and even self-driving cars.

Claude Code is our favorite AI coding agent. This course covers how Claude Code reads files, executes commands, and modifies code through its tool system, along with techniques for managing context, creating custom workflows, extending Claude Code with hooks, and integrating with external services.

In this course, you will learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You will learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you will experience how Gemini improves the application development workflow.

Elements of AI is the most popular course in the history of the University of Helsinki. It forms part of their free Artificial Intelligence Collection, which is arguably the most comprehensive and flexible set of free AI courses available from any university in the world. Depending on your background and what you are looking to achieve, there will be a module for you. From a simple introduction to the concepts of AI, all the way through to practical courses on machine learning and neural networks for developers.

Learn prompt engineering best practices for application development. Discover new ways to use large language models (LLMs), including how to build your own custom chatbot. Gain hands-on practice writing and iterating on prompts yourself using the OpenAI API.

In this course, you will learn the principles, techniques, and the best practices for designing effective prompts. This course introduces the basics of prompt engineering, and progresses to advanced prompt techniques. You will also learn how to guard against prompt misuse and how to mitigate bias when interacting with FMs..

This course introduces the fundamental ideas of natural language processing and language modelling, including how language models work, and how neural-based models are built. Learn about the key innovations that have enabled Transformer-based large language models to become dominant in solving various language tasks. Finally, learn about the challenges of applying these large language models to real-world problems.

Gain foundational knowledge, practical skills, and a functional understanding of how generative AI works. Dive into the latest research on Gen AI to understand how companies are creating value with cutting-edge technology. The course instructors are expert AWS AI practitioners who actively build and deploy AI in business use-cases.

In this curriculum, you will learn about the multiple approaches to Artificial Intelligence, and how the it has evolved from Knowledge Representation and reasoning (GOFAI) to Neural Networks and Deep Learning, which are at the core of modern AI. The concepts behind these important topics are explained using code in two of the most popular frameworks – TensorFlow and PyTorch.

In this course, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.

This developer tutorial includes a demo architecture and code snippets using SingleStore.

A detailed course that will set you on your way to becoming an AI Engineer by learning how to integrate AI into software applications. You’ll gain hands-on experience using APIs and open-source libraries to create AI-powered systems that deliver enhanced functionality and user experiences.

In this course you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system. You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation.

This detailed course forms part of Googles foundational machine learning courses for developers. They recommend taking the courses in order, but for developers that are already familiar with the basic concepts we suggest that you skip to the Crash Course module which they describe as ‘a fast-paced, practical introduction to machine learning, featuring a series of lessons with video lectures, real-world case studies, and hands-on practice exercises’. What we love in particular about this course are the Interactive visualizations which help to explain the concepts in an original and compelling way.

Agentic AI represents a new way of building software that leverages LLMs to complete some or all of the steps in complex tasks. Instead of generating single responses to prompts, agentic workflows enable AI to plan multi-step processes, execute them iteratively, and improve outputs through reflection and tool use. This course is designed to teach developers how to build these sophisticated AI systems from the ground up.

This is the introductory course in a series and is suitable for anyone with an interest in Agentic AI. The course introduces the fundamentals that underpin all later projects, covering the core concepts of AI agents, how they function, and why they represent a breakthrough in intelligent systems. Once completed you can move on to the next step which is to actually build your own multi-agent systems in the Building with CrewAI and LangChain course.

Consisting of six modules, this in-depth course explores AI’s place in product management – including how to leverage AI throughout the development life cycle, best practices for building AI-powered features, and why product managers should view AI as a strategic tool, not a threat.

This in-depth three course series provides a foundational understanding of how machine learning works and how it can be applied to solve problems. Participants will learn how to apply the data science process and how to lead machine learning projects that ensure privacy and ethical standards. The courses focus on the intuition behind these technologies, with no programming required, and merge theory with practical information including proven best practices from industry.

This unique course has been designed to equip the decision makers in any organization with the skills to both benefit from AI and transition their organizations to a future where machine learning will play an increasing role. Topics covered include Generative AI – Art of the Possible, Planning a Generative AI Project, and Building a Generative AI-ready organization.

This course is focused on providing project managers in all industries with practical skills and methods for using GenAI to improve the velocity, accuracy, and quality of their work. It recognizes that every project is unique and teaches how project managers can work with AI to improve productivity and results without losing the human touch.

In this comprehensive course experienced and will learn skills to identify real-world generative AI uses and popular generative AI models and tools for text, code, image, audio, and video. Learn all the skills and techniques required to boost your project manager career using generative AI.

This course covers how AI and machine learning can be practically applied in people management. You will explore concepts related to the role of data in machine learning, AI application, limitations of using data in HR decisions, and how bias can be mitigated using blockchain technology. By the end of this course participants will be able to identify how AI can be used to streamline all HR functions.

This extremely thorough course shows how AI can help with unique challenges like handling missing data and fully utilizing the vast amounts of data available. You’ll start by learning the nuances of working with 2D and 3D medical image data. You’ll then apply tree-based models to improve patient survival estimates. You’ll also use data from randomized trials to recommend treatments more suited to individual patients. Finally, you’ll explore how natural language extraction can more efficiently label medical datasets.

In this five-course series participants will learn about the current and future applications of AI in healthcare with the goal of learning how to introduce the technology into the clinical environment safely, ethically, and effectively. The final course in the series is a capstone project that provides a hands-on experience following a patient’s journey from the lens of the data, using a unique dataset created for this specialization.