Program profile · official sources
Generative AI for Beginners
Generative AI for Beginners (Version 3) is a 21-lesson course by Microsoft Cloud Advocates on the fundamentals of building generative AI applications, published as an open GitHub repository. Learn lessons explain concepts such as large language models, responsible AI and prompt engineering; Build lessons add Python and TypeScript code for text generation, chat, search, image generation, function calling, retrieval-augmented generation and AI agents. Each lesson has a short video introduction, a written lesson and extra resources. Basic Python or TypeScript knowledge is helpful, and the code runs on Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API or Foundry Local. No certificate is mentioned. As shown in the United States on 9 October 2026, the README states no price.
Facts checked 9 Oct 2026
- Price
- See pricing
No accepted price. The course README, as shown in the United States on 9 October 2026, states no price or fee for the course. To run the code it lists Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API, or Foundry Local, which it says runs models fully offline on your own device with no cloud subscription required; the cost of the cloud services is not stated on the README.
- Provider link
See the official page at Microsoft Cloud Advocates ↗
Official site. No commission.
- Time
- 21 lessons plus a Course Setup lesson (00); no hours or weeks are stated on the captured README
- Level
- Not listed
- Credential
- Not listed
- Prerequisites
- The README says basic knowledge of Python or TypeScript is helpful and points absolute beginners to separate Python and TypeScript courses; it lists a GitHub account to fork the repository, and access to Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API or Foundry Local to run the code.
- Format
- Self-paced online course published as an open GitHub repository and site: each lesson has a short video introduction, a written lesson in its README, Python and TypeScript code samples and links to extra resources
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
No accepted numeric price in this registry. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Course Setup
- Introduction to Generative AI and LLMs
- Exploring and comparing different LLMs
- Using Generative AI Responsibly
- Understanding Prompt Engineering Fundamentals
- Creating Advanced Prompts
- Building Text Generation Applications
- Building Chat Applications
- Building Search Apps Vector Databases
- Building Image Generation Applications
- Building Low Code AI Applications
- Integrating External Applications with Function Calling
- Designing UX for AI Applications
- Securing Your Generative AI Applications
- The Generative AI Application Lifecycle
- Retrieval Augmented Generation (RAG) and Vector Databases
- Open Source Models and Hugging Face
- AI Agents
- Fine-Tuning LLMs
- Building with SLMs
- Building with Mistral Models
- Building with Meta Models
Prerequisites: The README says basic knowledge of Python or TypeScript is helpful and points absolute beginners to separate Python and TypeScript courses; it lists a GitHub account to fork the repository, and access to Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API or Foundry Local to run the code.
What you actually do
- Course Setup : Lesson 00, Learn: How to Setup Your Development Environment (video marked Video Coming Soon) · Source
- Introduction to Generative AI and LLMs : Lesson 01, Learn: Understanding what Generative AI is and how Large Language Models (LLMs) work. · Source
- Exploring and comparing different LLMs : Lesson 02, Learn: How to select the right model for your use case · Source
- Using Generative AI Responsibly : Lesson 03, Learn: How to build Generative AI Applications responsibly · Source
- Understanding Prompt Engineering Fundamentals : Lesson 04, Learn: Hands-on Prompt Engineering Best Practices · Source
- Creating Advanced Prompts : Lesson 05, Learn: How to apply prompt engineering techniques that improve the outcome of your prompts. · Source
- Building Text Generation Applications : Lesson 06, Build: A text generation app using Azure OpenAI / OpenAI API · Source
- Building Chat Applications : Lesson 07, Build: Techniques for efficiently building and integrating chat applications. · Source
- Building Search Apps Vector Databases : Lesson 08, Build: A search application that uses Embeddings to search for data. · Source
- Building Image Generation Applications : Lesson 09, Build: An image generation application · Source
- Building Low Code AI Applications : Lesson 10, Build: A Generative AI application using Low Code tools · Source
- Integrating External Applications with Function Calling : Lesson 11, Build: What is function calling and its use cases for applications · Source
- Designing UX for AI Applications : Lesson 12, Learn: How to apply UX design principles when developing Generative AI Applications · Source
- Securing Your Generative AI Applications : Lesson 13, Learn: The threats and risks to AI systems and methods to secure these systems. · Source
- The Generative AI Application Lifecycle : Lesson 14, Learn: The tools and metrics to manage the LLM Lifecycle and LLMOps · Source
- Retrieval Augmented Generation (RAG) and Vector Databases : Lesson 15, Build: An application using a RAG Framework to retrieve embeddings from a Vector Databases · Source
- Open Source Models and Hugging Face : Lesson 16, Build: An application using open source models available on Hugging Face · Source
- AI Agents : Lesson 17, Build: An application using an AI Agent Framework · Source
- Fine-Tuning LLMs : Lesson 18, Learn: The what, why and how of fine-tuning LLMs · Source
- Building with SLMs : Lesson 19, Learn: The benefits of building with Small Language Models (video marked Video Coming Soon) · Source
- Building with Mistral Models : Lesson 20, Learn: The features and differences of the Mistral Family Models (video marked Video Coming Soon) · Source
- Building with Meta Models : Lesson 21, Learn: The features and differences of the Meta Family Models (video marked Video Coming Soon) · Source
Alternatives in the registry
Related by topic or level.
- Introduction to LLaMA : Check official price; 2 hours (provider headline; module and exam timings listed separately).
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- AI agent engineer : Check official price; 36 hours of content (provider-listed).
Change log
- : Initial record from the official course README captured from the United States on 9 October 2026. · Source
See the official page at Microsoft Cloud Advocates ↗
Official site. No commission.