Advanced RAG Micro-Credential

Advanced RAG Micro-Credential

Duration: 3-4 Hours

Description

A basic RAG pipeline — embed, retrieve, generate — gets a demo working in an afternoon and then plateaus well short of what production actually requires. This session picks up exactly there: hybrid retrieval that blends keyword and semantic search, reranking strategies that fix the wrong-but-plausible-looking result problem, and the pipeline tuning that separates a system that’s merely accurate from one that’s actually fast and cost-efficient at scale. Case studies cover where RAG pipelines break in real deployments — stale indexes, retrieval that quietly drifts off-topic, and evaluation that looks fine in testing but fails on real user queries — and how to catch each one before it reaches production.

Audience

This session assumes you’ve already built or worked with a basic RAG pipeline and hit its limits — not a first introduction to retrieval-augmented generation. It’s built for developers and ML practitioners responsible for taking a RAG proof-of-concept into production, where the questions shift from “does this work” to “is this fast, accurate, and affordable enough to run at real user volume.”

Objectives

  • Identify and implement advanced retrieval strategies to improve RAG system performance
  • Construct an optimized RAG pipeline for enhanced relevance and reduced latency
  • Apply techniques for evaluating, fine-tuning, and productionizing RAG models
  • Understand key considerations for scaling RAG systems for real-world applications

Prerequisites

This micro-credential is intended for experienced AI/ML engineers and researchers with a foundational understanding of LLMs, NLP, and vector databases.

Related AI Courses

See the full AI training roadmap and course directory for how this fits into a broader learning path.

New to RAG? Start with Beginner’s Guide to RAG Micro-Credential first. For a full multi-day treatment of advanced retrieval architecture, see RAG Deep Dive or Advanced Retrieval-Augmented Generation (RAG). Need a refresher on the vector search layer underneath RAG? See Introduction to Vector Databases for Developers Micro-Credential.

Course Outline

Module 1: The Optimized RAG Stack

  • RAG Beyond the Basics
  • Vector Search Mastery
  • The Power of Reranking
  • Lab – Identify Key Optimization Points in a Simple RAG Architecture

Module 2: Building and Fine-Tuning the Pipeline

  • Architecting an Optimizing Pipeline
  • The Fine-Tuning Imperative
  • Lab – A Practical RAG Implementation
  • Addressing the Hallucination Problem

Module 3: Performance, Deployment, and Scale

  • Evaluating Your RAG System
  • Latency and Throughput Optimization
  • From Prototype to Production
  • Case Studies