Enabling Full-Stack GenAI Engineers
Searching Your GenAI Data Series
Certification Series
How strong are your GenAI search capabilities when accuracy, intelligence, and trust matter most?
As GenAI assistants and copilots become primary interfaces to data, search quality increasingly determines how intelligent and reliable those systems feel to users.
To Win, your GenAI solutions must combine strong search fundamentals with modern retrieval techniques that consistently surface the right information.
The Challenge
Without a strong, end-to-end approach to searching GenAI data, solutions struggle to:
- Surface relevant information across unstructured, structured, and distributed data sources.
- Combine semantic understanding with precise filtering, ranking, and control.
- Support multi-step reasoning and agent-driven workflows without compounding errors. Gaps across this search lifecycle will drive hallucinations, incomplete answers, brittle automation, and frustrated users.
Our Solution
The Searching Your GenAI Data Series Certification focuses on building strong, production-ready GenAI search capabilities. Participants will:
- Explore keyword, semantic, hybrid, and graph-based search techniques using realistic datasets.
- Apply hands-on labs and curated notebooks to integrate search tools into GenAI workflows.
- Build an end-to-end search strategy that supports multi-step reasoning, agents, and production-scale retrieval.
Area of Focus
- Foundational Keyword & Semantic Search — Combine lexical precision with semantic understanding for reliable retrieval.
- Tool Integration & Agentic Search — Orchestrate search tools inside agent-driven GenAI workflows.
- Multi-Step Approaches — Design chained retrieval strategies that support reasoning across multiple queries.
- Fusion Search — Blend results from multiple retrieval methods into a single ranked response.
- Embedding & Metadata Search Techniques — Improve relevance using embeddings, filters, and contextual signals.
- Structured & Graph-Based Data Search — Search tables, graphs, and relational data with semantic intent.
- Distributed Search — Retrieve and rank information across large, decentralized data environments.
Skills You'll Gain
- End-to-End GenAI Search Design - Architect retrieval systems that support accurate, explainable GenAI responses.
- Higher Retrieval Precision - Reduce hallucinations by consistently grounding answers in the right data.
- Hybrid Search Strategies - Combine keyword, semantic, and structured approaches effectively.
- Agent-Ready Search Pipelines - Enable GenAI agents to plan, query, and refine searches safely.
- Production Search Readiness - Build scalable, debuggable retrieval systems suitable for real-world use.