GitHub

Generative AI for Beginners - A Course

What is the project about?

This project is a comprehensive 21-lesson course designed to teach the fundamentals of building Generative AI applications. It covers a wide range of topics, from the basics of Generative AI and Large Language Models (LLMs) to advanced concepts like prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.

What problem does it solve?

The course addresses the growing need for accessible education in the field of Generative AI. It provides a structured learning path for beginners to understand and start building their own Generative AI applications. It demystifies complex concepts and provides practical, hands-on experience.

What are the features of the project?

  • 21 Lessons: Covering various aspects of Generative AI.
  • Learn and Build Lessons: A mix of theoretical ("Learn") and practical ("Build") lessons.
  • Code Samples: Examples in both Python and TypeScript (where applicable).
  • Multiple Model Support: Guidance on using Azure OpenAI Service, GitHub Marketplace Model Catalog, and OpenAI API.
  • Beginner-Friendly: Assumes basic Python or TypeScript knowledge, with links to introductory courses for absolute beginners.
  • Community Support: Access to an AI Discord server for learner interaction and support.
  • Startup Support: Information on Microsoft for Startups Founders Hub for potential free credits.
  • Open for Contributions: Encourages community involvement through issues and pull requests.
  • Video Introductions: Each lesson has a short video overview.
  • Further Learning: "Keep Learning" sections with additional resources.

What are the technologies used in the project?

  • Programming Languages: Python, TypeScript.
  • AI Services: Azure OpenAI Service, OpenAI API, GitHub Marketplace Model Catalog.
  • Models: Various LLMs, including those from OpenAI, Mistral, and Meta, as well as open-source models from Hugging Face.
  • Concepts/Frameworks: Prompt Engineering, Retrieval Augmented Generation (RAG), Vector Databases, AI Agents, Fine-tuning, Function Calling.
  • Low-Code Platforms: Mentions building applications with low-code tools.

What are the benefits of the project?

  • Accessible Learning: Provides a structured and beginner-friendly approach to learning Generative AI.
  • Practical Skills: Equips learners with the ability to build real-world applications.
  • Comprehensive Coverage: Addresses a wide range of relevant topics.
  • Community and Support: Fosters a learning community and provides support channels.
  • Up-to-Date: Covers current technologies and best practices.
  • Open Source: Allows for community contributions and improvements.

What are the use cases of the project?

  • Education: Serving as a primary learning resource for individuals new to Generative AI.
  • Skill Development: Helping developers upskill and expand their capabilities.
  • Prototyping: Enabling rapid prototyping of Generative AI applications.
  • Application Building: Providing the foundation for building various types of Generative AI applications, including:
    • Text generation applications
    • Chat applications
    • Search applications
    • Image generation applications
    • Low-code AI applications
    • Applications integrated with external services (via function calling)
generative-ai-for-beginners screenshot