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The RAG Stack: Retrieval-Augmented Generation in Production
The RAG Stack: Retrieval-Augmented Generation in Production
Prompt Web
Original price was: A$110.08.Current price is: A$92.40.
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The RAG Stack: Retrieval-Augmented Generation in Production
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The RAG Stack: Retrieval-Augmented Generation in Production

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Original price was: A$110.08.Current price is: A$92.40.

Build AI applications that answer questions from your own documents, databases, and knowledge bases — accurately.

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RAG is the dominant architecture for enterprise AI applications in 2026. This course covers the full RAG stack: embedding models, vector databases, retrieval pipelines, reranking, and LLM integration. You’ll build a production-grade document Q&A system from scratch and learn to evaluate it rigorously. Every component is explained from first principles, not just configuration.

✅ What’s Inside:

  1. What is RAG and Why It Dominates
  2. Text Embeddings Explained
  3. Vector Databases Compared
  4. Chunking Strategies for Documents
  5. Semantic vs Keyword Search
  6. Hybrid Retrieval Methods
  7. Reranking with Cross-Encoders
  8. LLM Integration Layer
  9. Handling Long Contexts
  10. Evaluation: RAG Metrics
  11. Scaling the Pipeline
  12. Full Project: Document Intelligence App
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