Extending LLM models using Azure services and tools
What you'll learn
Understand key concepts of RAG
Develop practical, hands-on skills
Getting familiar with Azure AI tools and services
Extend LLM models with data
Requirements
Basic programming in Python and Notebooks
Basic knowledge in Azure services
No required knowledge in LLMs or ML
Description
[This course is still yet under development and the current release is a Beta test intended for getting feedback]Elevate your development skills with our specialized course designed for developers and IT professionals. This course focuses on the essentials of Retrieval-Augmented Generation (RAG) using Azure's cutting-edge tools and services.Throughout this course, you will:Understand RAG Fundamentals: Learn the core principles of Retrieval-Augmented Generation and its applications.Utilize Azure AI Studio: Gain hands-on experience with Azure AI Studio to build and deploy AI models.Leverage LLM Models like ChatGPT: Integrate and utilize large language models, including ChatGPT, for advanced AI solutions.Embed Vectors with AI Search Service: Master the techniques of embedding vectors and enhancing search capabilities using Azure AI Search service.Use RAG flow with Azure AI Studio: Create your own RAG application with few clicks from the AI Studio.By the end of this course, you will have the skills to implement RAG solutions effectively, leveraging Azure's powerful tools and services. Whether you're looking to advance your career or enhance your technical expertise, this course provides the knowledge and practical experience you need to succeed in the rapidly evolving field of AI and machine learning.Join us and become proficient in the latest AI technologies with Azure!
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Introduction to RAG[Presentation]
Lecture 3[Demo] Creating Azure resources using the portal
Lecture 4[Demo] Creating Azure resources using command line
Lecture 5[Demo] Connecting to OpenAI ChatGPT model
Lecture 6[Demo] Counting the tokens for all documents
Lecture 7[Demo] Cleaning the markdown files
Lecture 8[Demo] Creating the embedding vector
Lecture 9[Demo] Chunking the documents to lower the number of tokens
Lecture 10[Demo] Creating Search Index in Azure AI Search
Lecture 11[Demo] Uploading the chunks to AI Search
Lecture 12[Demo] Searching using Vector embedding
Lecture 13[Demo] Chatting with ChatGPT with documents
Section 2: RAG made simple in Azure AI Studio
Lecture 14 Introduction to RAG inside Azure AI Studio
Lecture 15[Demo] Configuring RAG in AI Studio
Lecture 16[Demo] Exploring RAG with ChatGPT model
Beginner developers who looking for understanding and learning RAG/AI apps,Beginner non-developers looking for an easy way to use LLMs in their company,Anyone looking for creating his own Copilot
Screenshots

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