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AI Training
Generative AI for IT & Technical Teams
A technical grounding in models, integration patterns, and operational tradeoffs.
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Scope, tools, duration, and availability are agreed for each engagement; these outlines are not records of past delivery.
Overview
Examine how LLM applications are assembled and why model capability alone is insufficient. Connect data boundaries, evaluation, observability, and access controls to practical system choices.
Learning outcomes
- Explain common LLM application patterns
- Evaluate integration and data risks
- Outline practical evaluation checks
Example topics
- LLM APIs and prompt architecture
- RAG, embeddings, and vector search concepts
- Structured output and tool use
- Evaluation, observability, and security
Who should attend
IT professionals, engineers, architects, and technical leads.
Format & customization
Technical demonstrations and architecture exercises; depth is tailored to the team.
This outline can be adapted to the audience, industry, approved tools, duration, and practical use cases. Final scope is agreed before an engagement.
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