Schema-Aware Retrieval for RAG Systems | AI Product Development Courses

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Издатель Apr 8, 2026

Retrieval-Augmented Generation (RAG) is the standard for LLM applications, but pure vector search breaks when users ask for structured or filtered data (like "show me all high-priority billing issues from last month"). Vector search cannot apply date ranges, distinguish categories, or reliably filter by structured attributes.

This course, Schema-Aware Retrieval for RAG Systems, is designed to help you solve these production-level retrieval problems by building systems that understand data structure *before* running semantic search.

What You Will Learn:
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- Solve Vector Search Failure: Understand why naive vector search fails on structured queries and the exact conditions that cause it.
- Schema & Chunking: Learn to identify and work with real-world schema types (tabular, JSON, relational, document-store). Master schema-aware chunking strategies (field-level, record-level, hybrid) that preserve structured metadata.
- Multi-Index Architecture: Design and combine purpose-appropriate indexes—hash, inverted, range, and vector—into an efficient multi-index retrieval store.
- Advanced Query Parsing: Parse natural language queries into structured filters using rule-based regex and LLM-based tool calling.
- Hybrid Retrieval: Implement advanced strategies like filter-then-rank, multi-field retrieval, BM25 + vector hybrid search using Reciprocal Rank Fusion, and progressive fallback chains.
- Build an Engine: Assemble a complete query engine from scratch that handles both structured and unstructured queries accurately and degrades gracefully on edge cases.
- Evaluation: Measure retrieval performance using standard metrics (precision, recall) to validate your pipeline against real-world quality standards.

This course is for RAG developers who have hit a ceiling with basic vector search, AI/ML engineers, backend developers integrating LLMs with structured databases, and anyone preparing for applied AI engineering roles. Prerequisites include a solid working knowledge of Python and a basic understanding of text embeddings.

Enroll now: https://www.ai.codersarts.com/courses/schema-aware-retrieval-for-rag-systems