| File Name: | LLM APPLICATION ARCHITECTURE ON AZURE |
| Content Source: | https://www.udemy.com/course/rag-agentic-ai-on-azure/?couponCode=LETSLEARNNOW |
| Genre / Category: | Other Tutorials |
| File Size : | 721.3 MB |
| Publisher: | Alireza Chegini |
| Updated and Published: | July 9, 2025 |
This course gives you a practical, architecture-focused pathway to master Retrieval-Augmented Generation (RAG) and architect advanced LLM applications on Azure’s AI ecosystem. Whether you’re a developer, architect, or product manager, this course helps you design, build, and deploy context-aware AI systems that are secure, scalable, and enterprise-ready.
RAG ARCHITECTURE AS THE CORE AI PATTERN
Unlike general LLM courses, this program is laser-focused on Retrieval-Augmented Generation as a modern architecture pattern. You’ll understand:
- Why RAG is essential to combat hallucinations
- How it grounds responses using enterprise data
- How to integrate Azure services like Azure AI Search, Azure OpenAI, and vector databases into the pipeline
FROM CONCEPTS TO PRODUCTION-READY DEPLOYMENT
We begin with the fundamentals of LLMs—what they are good at, where they fail, and how RAG bridges the gap. But this course goes much further.
You will learn:
- Key LLM application architecture concepts on Azure
- The differences between LLM apps and RAG solutions
- How to extend LLM apps into agentic architectures by incorporating tools and dynamic data sources
Who this course is for:
- Product managers, analysts, and business leaders looking to understand the LLM Architecture concept and how RAG enables trustworthy AI assistants.
- Cloud developers and solution architects who want to design reliable AI applications using LLMs.
- Technical teams evaluating Azure AI services like OpenAI, AI Search, and Copilot Studio for internal copilots.
- Anyone interested in building AI-powered chatbots that are grounded in real business documents and data—no prior AI experience required.
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