Boost your AI knowledge and skills with these free online courses

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 is an introductory-level microlearning course aimed at explaining what responsible AI is, why it’s important, and how Google implements responsible AI in their products. It also introduces Google’s 7 AI principles.

Learn how the Gen AI capabilities of Bing Chat can help you perform a wide variety of tasks from generating ideas and summarizing data to solving common work problems such as planning itineraries, scheduling, and communicating with coworkers.

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 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.

This comprehensive course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation.

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.

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.