Back to AI DashboardModule 6: RAG Engineering
AI Engineer Track
Module 6: RAG Engineering
Build robust retrieval-augmented pipelines integrating document loaders, rerankers, and retrieval evaluations.
Syllabus Modules
Retrieval-Augmented OverviewComing Soon
Verify core retrieval, prompt packing, and inference pipeline workflows.
Total Lessons: 0Explore Module
Document LoadersComing Soon
Parse structured layout PDF, CSV, and doc metadata formats.
Total Lessons: 0Explore Module
Query RewritingComing Soon
Setup prompt expansion rewriting user inputs semantically.
Total Lessons: 0Explore Module
Reranking PipelinesComing Soon
Integrate cross-encoders evaluating retrieved text matches relevance.
Total Lessons: 0Explore Module
RAG EvaluationsComing Soon
Measure faithfulness and context recall score targets.
Total Lessons: 0Explore Module
Track Progress
0 / 6Projects Verified
Learning Outcomes
- Reduce hallucinations by optimizing prompt retrieval context
- Integrate cross-encoder rerankers to improve search recall
- Construct ragas evaluation datasets evaluating faithfulness
Interview Defense
- Describe how query expansion resolves vocabulary mismatch in RAG pipelines
- Propose strategies to protect database access controls in dynamic user RAG queries