Enabling Full-Stack GenAI Engineers
Retrieving Your GenAI Data Series
Certification Series
How reliably do your GenAI solutions retrieve the right context to reason, answer, and act?
As GenAI systems move into production, retrieval quality has become a primary driver of accuracy, trust, and usefulness. Even strong models fail when the right information is not retrieved, ranked, and supplied at the right moment.
To Win, your GenAI solutions must retrieve high-quality context consistently, rank it intelligently, and support reliable reasoning across real-world data.
The Challenge
Without a strong, end-to-end approach to GenAI context retrieval, solutions struggle to:
- Surface the most relevant information from large, noisy, or mixed data sources.
- Balance precision, recall, and latency as systems scale.
- Control ranking quality and reduce downstream hallucinations. Gaps across this retrieval lifecycle will drive incorrect answers, brittle reasoning, and GenAI systems that cannot be trusted in production.
Our Solution
The Retrieving Your GenAI Data Series Certification is a workshop series focused on mastering modern context retrieval and ranking techniques for GenAI systems. Participants will:
- Explore traditional, hybrid, and advanced retrieval strategies using realistic datasets.
- Apply hands-on labs and curated notebooks to tune retrieval, ranking, and fusion behavior.
- Build an end-to-end retrieval pipeline that reliably supplies high-quality context to GenAI solutions.
Area of Focus
- Traditional & Hybrid Retrieval — Combine keyword, vector, and hybrid approaches to balance precision and recall.
- Advanced / Specialized Retrieval Strategies — Apply domain-specific, task-aware, and constrained retrieval techniques.
- Re-Ranking & Fusion Methods — Improve answer quality by intelligently ranking and blending retrieved results.
Skills You'll Gain
- Reliable Context Retrieval Design - Architect retrieval pipelines that consistently supply relevant information.
- Improved Ranking Quality - Reduce hallucinations by delivering better-ordered, higher-signal context.
- Hybrid Retrieval Strategies - Combine multiple retrieval methods to handle real-world data complexity.
- Retrieval Debugging & Tuning - Diagnose gaps in recall, ranking, and relevance with confidence.
- Production Retrieval Readiness - Build scalable, controllable retrieval systems suitable for live GenAI applications.