Retrieval Augmented Generation (RAG) with Azure AI Search
Hallucinations are killing production GenAI deployments—and RAG is the proven antidote. This course teaches you how to ground large language models with real data using Azure AI Search, enabling you to build enterprise-grade systems that actually know what they’re talking about.
AIU.ac Verdict: Essential for engineers and architects building production GenAI solutions who need to move beyond basic prompting. You’ll gain hands-on skills in Azure’s retrieval stack, though the 29-minute runtime means this is a focused primer rather than a deep-dive certification.
What This Course Covers
You’ll explore the core mechanics of Retrieval Augmented Generation—why it matters, how it reduces model hallucinations, and when to use it over fine-tuning. The course walks through Azure AI Search integration, vector indexing, semantic ranking, and the practical pipeline of chunking, embedding, and retrieval-augmented prompting.
Expect practical demonstrations of building a RAG system end-to-end: preparing documents, configuring search indices, querying with context injection, and evaluating retrieval quality. You’ll understand the trade-offs between retrieval speed, relevance, and cost—critical for scaling from proof-of-concept to production.
Who Is This Course For?
Ideal for:
- GenAI engineers and ML engineers: Building production LLM applications who need to ground models with proprietary data and reduce hallucinations immediately.
- Solution architects and tech leads: Evaluating Azure AI Search for enterprise GenAI initiatives and need to understand RAG architecture and implementation patterns.
- Data engineers transitioning to GenAI: Familiar with indexing and search who want to understand how retrieval fits into modern LLM workflows.
May not suit:
- Complete beginners to AI/ML: Assumes familiarity with LLMs, embeddings, and Azure fundamentals. Start with foundational GenAI courses first.
- Researchers seeking theoretical depth: This is a practical implementation course, not an academic exploration of RAG algorithms or advanced retrieval theory.
Frequently Asked Questions
How long does Retrieval Augmented Generation (RAG) with Azure AI Search take?
29 minutes. It’s a focused, practical course designed for busy professionals. Ideal for upskilling quickly or as a primer before deeper hands-on labs.
Do I need Azure experience to take this course?
Yes—you should be comfortable with Azure basics and have worked with cloud services. The course assumes you can navigate the Azure portal and understand cloud resource provisioning.
Will this course teach me to build a production RAG system?
This course covers the core concepts and Azure AI Search integration. For a complete production system, you’ll likely pair this with hands-on labs, documentation, and experience with your specific data pipeline and LLM choice.
Is this course vendor-locked to Azure?
Yes—it focuses specifically on Azure AI Search. The RAG principles are transferable, but implementation details are Azure-specific. Other platforms (Pinecone, Weaviate, etc.) have different tooling.
Course by Harit Himanshu on Pluralsight. Duration: 0h 29m. Last verified by AIU.ac: March 2026.
