Skip to content
Description: A globally popular, non-technical introduction to AI, combining theory and practical exercises. No coding required.Learning Objectives: Understand what AI is, its capabilities and limitations, and how it impacts society.Why Recommended: Accessible to all backgrounds, available in multiple languages, and highly acclaimed for demystifying AIDescription: A 6-hour course for non-technical learners covering AI basics, business applications, and societal implications.Learning Objectives: Grasp core AI terminology, recognize AI’s realistic capabilities, and identify opportunities to use AI in your work.Why Recommended: Taught by a leading AI educator, requires no technical background, and is free to auditDescription: A modular course introducing AI concepts, natural language processing, and ethical considerations.Learning Objectives: Gain foundational AI knowledge, understand practical applications, and build a simple chatbot.Description: A 12-week, 24-lesson curriculum with practical labs and quizzes, hosted on GitHub.Learning Objectives: Learn AI concepts, build basic AI models, and understand ethical issues.Description: A short course explaining generative AI and large language models.Learning Objectives: Understand generative AI, LLMs, and responsible AI principles.
Description: A 12-lesson course covering generative AI, prompt engineering, and app-building.Learning Objectives: Build generative AI apps, use LLMs, and apply prompt engineering.Description: A 7-hour course on crafting and optimizing prompts for generative AI.Learning Objectives: Write effective prompts, troubleshoot AI outputs, and apply to real-world tasks.Description: A self-paced learning path with labs on generative AI tools and prompt design.Learning Objectives: Use Google’s generative AI tools, design prompts, and build simple AI solutions.
Description: A 10-hour course on fine-tuning, integrating, and deploying LLMs in projects.Learning Objectives: Fine-tune LLMs, integrate them into applications, and handle advanced AI tasks.Description: Self-paced courses on deep learning and GPU programming.Learning Objectives: Build and train deep learning models, optimize with GPUs, and tackle real-world AI challenges.Why Recommended: Industry-grade, hands-on labs, and ideal for those with strong coding backgrounds
Summary: OpenAI Academy is a free, public learning hub designed to boost AI literacy for all audiences, including educators, students, nonprofit leaders, and small-business owners. It features expert-led workshops, on-demand videos, and community discussions covering AI fundamentals, prompt engineering, advanced integration, and real-world use cases. The platform is continuously updated with new resources and live events, aiming to democratize AI knowledge and empower users to integrate AI responsibly and effectively into their work and communitiesKey Content Areas:Mastering PromptsIntroduction to Prompt EngineeringEvals for production-ready AI appsCustom GPTsAI Policy in SchoolsAdvanced Features for NonprofitsK-12 and Higher Education resources
Summary: OpenAI provides comprehensive API documentation and hands-on tutorials for developers and technical professionals. These resources guide users through integrating models like GPT-4, DALL-E, and Whisper, covering topics such as authentication, rate limits, prompt engineering, and building real AI apps (e.g., website Q&A, meeting transcription). The documentation is practical, well-structured, and regularly updated with new examples and guidesKey Content Areas:API integration and best practicesStep-by-step app buildingPrompt engineeringFine-tuning modelsDynamic code examples
Summary: The OpenAI Cookbook is a collection of code samples and practical guides for developers working with OpenAI’s APIs. It covers common use cases such as text summarization, image generation, and fine-tuning, providing hands-on starting points for experimentation and rapid prototypingKey Content Areas:Code examples for GPT, DALL-E, WhisperPrompt design and optimizationFine-tuning workflowsIntegration tips
Summary: OpenAI publishes research papers, technical blog posts, and case studies that explain the capabilities, limitations, and ethical considerations of its models. These materials help users understand the science behind AI, stay updated on the latest advancements, and learn from real-world applicationsKey Content Areas:Model updates and safety featuresReinforcement learning and alignmentIndustry case studiesResponsible AI practices
Summary: OpenAI’s community forum is an active space where users can ask questions, share insights, troubleshoot issues, and discuss AI ethics and applications. It supports collaborative learning and knowledge exchange among developers and researchersKey Content Areas:Developer Q&AUse case sharingTroubleshootingEthical discussions
Authoritative: All resources are either created or directly supported by OpenAI.Practical: They offer hands-on guides, real-world examples, and community support.Accessible: Most materials are free and designed for a wide range of users, from beginners to advanced developers.Current: Content is regularly updated to reflect the latest in AI technology and practices.
Summary: OpenAI Academy is a free, public learning hub designed to boost AI literacy for all audiences, including educators, students, nonprofit leaders, and small-business owners. It features expert-led workshops, on-demand videos, and community discussions covering AI fundamentals, prompt engineering, advanced integration, and real-world use cases. The platform is continuously updated with new resources and live events, aiming to democratize AI knowledge and empower users to integrate AI responsibly and effectively into their work and communitiesKey Content Areas:Mastering PromptsIntroduction to Prompt EngineeringEvals for production-ready AI appsCustom GPTsAI Policy in SchoolsAdvanced Features for NonprofitsK-12 and Higher Education resources
Summary: OpenAI provides comprehensive API documentation and hands-on tutorials for developers and technical professionals. These resources guide users through integrating models like GPT-4, DALL-E, and Whisper, covering topics such as authentication, rate limits, prompt engineering, and building real AI apps (e.g., website Q&A, meeting transcription). The documentation is practical, well-structured, and regularly updated with new examples and guidesKey Content Areas:API integration and best practicesStep-by-step app buildingPrompt engineeringFine-tuning modelsDynamic code examples
Summary: The OpenAI Cookbook is a collection of code samples and practical guides for developers working with OpenAI’s APIs. It covers common use cases such as text summarization, image generation, and fine-tuning, providing hands-on starting points for experimentation and rapid prototypingKey Content Areas:Code examples for GPT, DALL-E, WhisperPrompt design and optimizationFine-tuning workflowsIntegration tips
Summary: OpenAI publishes research papers, technical blog posts, and case studies that explain the capabilities, limitations, and ethical considerations of its models. These materials help users understand the science behind AI, stay updated on the latest advancements, and learn from real-world applicationsKey Content Areas:Model updates and safety featuresReinforcement learning and alignmentIndustry case studiesResponsible AI practices
Summary: OpenAI’s community forum is an active space where users can ask questions, share insights, troubleshoot issues, and discuss AI ethics and applications. It supports collaborative learning and knowledge exchange among developers and researchersKey Content Areas:Developer Q&AUse case sharingTroubleshootingEthical discussions
Authoritative: All resources are either created or directly supported by OpenAI.Practical: They offer hands-on guides, real-world examples, and community support.Accessible: Most materials are free and designed for a wide range of users, from beginners to advanced developers.Current: Content is regularly updated to reflect the latest in AI technology and practices.
What is an LLM?
LLM Explained
How LLM’s Work
Go learn!
Here are 10 free AI training courses suitable for three levels of adult learners—beginner, intermediate, and advanced. Each listing includes the URL, a brief description, learning objectives, and reasons for recommendation.
Beginner Level
1. Elements of AI (University of Helsinki & MinnaLearn)
.2. AI for Everyone (Andrew Ng, Coursera)
.3. IBM SkillsBuild: Artificial Intelligence Fundamentals
4. Microsoft: AI for Beginners
5. Google: Introduction to Generative AI
Intermediate Level
6. Microsoft: Generative AI for Beginners
7. IBM: Generative AI—Prompt Engineering Basics (Coursera)
8. Google Cloud: Generative AI Learning Path
Advanced Level
9. DeepLearning.AI: Building with Large Language Models (Coursera)
10. NVIDIA: Fundamentals of Deep Learning
.These courses were chosen for their accessibility, practical focus, and strong reputations. They cover a spectrum from foundational knowledge to advanced, hands-on AI development, ensuring relevance for adult learners at any stage.
Here is a summary of OpenAI’s official training materials, including URLs and concise descriptions:
1. OpenAI Academy
.2. OpenAI API Documentation & Tutorials
.3. OpenAI Cookbook (GitHub)
.4. OpenAI Research, Blogs, and Case Studies
.5. Community Forums and Support
.Why These Materials Are Recommended
These resources collectively provide a strong foundation for anyone looking to understand, implement, or teach with OpenAI’s tools and models.
Here is a summary of OpenAI’s official training materials, including URLs and concise descriptions:
1. OpenAI Academy
.2. OpenAI API Documentation & Tutorials
.3. OpenAI Cookbook (GitHub)
.4. OpenAI Research, Blogs, and Case Studies
.5. Community Forums and Support
.Why These Materials Are Recommended
These resources collectively provide a strong foundation for anyone looking to understand, implement, or teach with OpenAI’s tools and models.
Want to print your doc?
This is not the way.
This is not the way.
Try clicking the ··· in the right corner or using a keyboard shortcut (
CtrlP
) instead.