Free Generative AI Courses
Dive into the transformative world of Generative AI with this expertly curated selection of free courses from leading tech giants. Whether you’re just starting out or looking to deepen your expertise, these modules offer something for everyone. From Google's foundational insights into large language models and responsible AI principles to AWS's practical guidance on AI project planning, and Nvidia's advanced explorations of retrieval-augmented generation, this learning path provides a comprehensive overview of the latest in AI technology.
Certificate Course
AI for EveryoneLearn the basics of Artificial Intelligence and start using AI in your career. This course will teach you the business aspects of AI. Learn more >
Google | Beginner: Introduction to Generative AI Learning Path - Free
A series of learning modules that provides an overview of generative AI concepts, from the fundamentals of large language models to responsible AI principles. Enroll >>
01 - Introduction to Generative AI - 45 mins
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. Enroll >>
02 Introduction to Large Language Models - 30 mins
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. Enroll >>
03 - Introduction to Responsible AI - 30 mins
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. Enroll >>
04 - Prompt Design in Vertex AI - 5 hrs 15 mins
Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Enroll >>
05 - Responsible AI: Applying AI Principles with Google Cloud - 2 hrs
This course, Responsible AI: Applying AI Principles with Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Responsible AI: Applying AI Principles with Google Cloud. Enroll >>
01 - Introduction to Generative AI - 45 mins
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. Enroll >>
02 Introduction to Large Language Models - 30 mins
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. Enroll >>
03 - Introduction to Responsible AI - 30 mins
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. Enroll >>
04 - Prompt Design in Vertex AI - 5 hrs 15 mins
Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Enroll >>
05 - Responsible AI: Applying AI Principles with Google Cloud - 2 hrs
This course, Responsible AI: Applying AI Principles with Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Responsible AI: Applying AI Principles with Google Cloud. Enroll >>
Introduction to Generative AI
Free AI Courses for Developers
AI Python for BeginnersLearn Python programming fundamentals and how to integrate AI tools for data manipulation, analysis, and visualization. Discover how Python can be applied in various domains such as business, marketing, and journalism to solve real-world problems and enhance efficiency through practical applications. Leverage AI assistants to debug code, explain concepts, and enhance your learning, mirroring real-world software development practices. Learn more >
ChatGPT Prompt Engineering for DevelopersLearn prompt engineering best practices for application development. Discover new ways to use LLMs, including how to build your own custom chatbot. Gain hands-on practice writing and iterating on prompts yourself using the OpenAI API.
Learn more >
AWS | Generative AI Free Courses
Introduction to Generative AI: Art of the Possible - 1 hr
The Introduction to Generative AI - Art of the Possible course provides an introduction to generative AI, use cases, risks and benefits. With the help of a content generation example, we illustrate the art of the possible. By the end of the course, learners should be able to describe the basics of generative AI, its risks and benefits. They should also be able to articulate how content generation can be used in their business. Enroll >>
Generative AI for Executives - 45 Mins
Generative AI for Executives (eLearning) provides a high-level picture of generative AI. Learners explore what generative AI is, how it can address executives’ concerns and challenges, and how it supports business growth. They also learn how generative AI has the potential to revolutionize numerous industries. Enroll >>
Planning a Generative AI Project - 1 hr
Planning a Generative AI Project is the second course in the three-part series called Generative AI Essentials for Business and Technical Decision Makers. If you have not done so already, start with the first course in the series, Introduction to Generative AI - Art of the Possible. Enroll >>
The Introduction to Generative AI - Art of the Possible course provides an introduction to generative AI, use cases, risks and benefits. With the help of a content generation example, we illustrate the art of the possible. By the end of the course, learners should be able to describe the basics of generative AI, its risks and benefits. They should also be able to articulate how content generation can be used in their business. Enroll >>
Generative AI for Executives - 45 Mins
Generative AI for Executives (eLearning) provides a high-level picture of generative AI. Learners explore what generative AI is, how it can address executives’ concerns and challenges, and how it supports business growth. They also learn how generative AI has the potential to revolutionize numerous industries. Enroll >>
Planning a Generative AI Project - 1 hr
Planning a Generative AI Project is the second course in the three-part series called Generative AI Essentials for Business and Technical Decision Makers. If you have not done so already, start with the first course in the series, Introduction to Generative AI - Art of the Possible. Enroll >>
Certificate Courses
Generative AI for Product ManagersElevate your Product Manager career with Gen AI. Build in-demand hands-on generative AI skills to boost your Product...
Boost your software development career with Gen AI. Build in-demand hands-on Generative AI skills for your...
Nvidia - Beginner to Advanced Free AI Courses
Generative AI Explained - 2 hrs
Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent time, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, applications, as well as the challenges and opportunities in this exciting field. Enroll >>
Building RAG Agents with LLMs - 8 hrs
The evolution and adoption of large language models (LLMs) have been nothing short of revolutionary, with retrieval-based systems at the forefront of this technological leap. These models are not just tools for automation; they are partners in enhancing productivity, capable of holding informed conversations by interacting with a vast array of tools and documents. This course is designed for those eager to explore the potential of these systems, focusing on practical deployment and the efficient implementation required to manage the considerable demands of both users and deep learning models. As we delve into the intricacies of LLMs, participants will gain insights into advanced orchestration techniques that include internal reasoning, dialog management, and effective tooling strategies. Enroll >>
Augment your LLM Using Retrieval Augmented Generation - 1 hr
Retrieval Augmented Generation (RAG) - Introduced by Facebook AI Research in 2020, is an architecture used to optimize the output of an LLM with dynamic, domain specific data without the need of retraining the model. RAG is an end-to-end architecture that combines an information retrieval component with a response generator. In this introduction we provide a starting point using components we at NVIDIA have used internally. This workflow will jumpstart you on your LLM and RAG journey. Enroll >>
Introduction to Physics-informed Machine Learning with Modulus - 4 hrs
High-fidelity simulations in science and engineering are computationally expensive and time-prohibitive for quick iterative use cases, from design analysis to optimization. NVIDIA Modulus, the physics machine learning platform, turbocharges such use cases by building physics-based deep learning models that are 100,000x faster than traditional methods and offer high-fidelity simulation results. Enroll >>
Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent time, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, applications, as well as the challenges and opportunities in this exciting field. Enroll >>
Building RAG Agents with LLMs - 8 hrs
The evolution and adoption of large language models (LLMs) have been nothing short of revolutionary, with retrieval-based systems at the forefront of this technological leap. These models are not just tools for automation; they are partners in enhancing productivity, capable of holding informed conversations by interacting with a vast array of tools and documents. This course is designed for those eager to explore the potential of these systems, focusing on practical deployment and the efficient implementation required to manage the considerable demands of both users and deep learning models. As we delve into the intricacies of LLMs, participants will gain insights into advanced orchestration techniques that include internal reasoning, dialog management, and effective tooling strategies. Enroll >>
Augment your LLM Using Retrieval Augmented Generation - 1 hr
Retrieval Augmented Generation (RAG) - Introduced by Facebook AI Research in 2020, is an architecture used to optimize the output of an LLM with dynamic, domain specific data without the need of retraining the model. RAG is an end-to-end architecture that combines an information retrieval component with a response generator. In this introduction we provide a starting point using components we at NVIDIA have used internally. This workflow will jumpstart you on your LLM and RAG journey. Enroll >>
Introduction to Physics-informed Machine Learning with Modulus - 4 hrs
High-fidelity simulations in science and engineering are computationally expensive and time-prohibitive for quick iterative use cases, from design analysis to optimization. NVIDIA Modulus, the physics machine learning platform, turbocharges such use cases by building physics-based deep learning models that are 100,000x faster than traditional methods and offer high-fidelity simulation results. Enroll >>
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