Applied AI & Emerging Tech Integration

AI developer tooling, code generation verification, prompt hygiene, and machine learning fundamentals.

On the exams

How this domain is tested

The share of each exam, and what the domain covers at that level.

AI developer tooling, code generation verification, prompt hygiene, and machine learning fundamentals

RAG system topologies, vector databases, enterprise AI security, and the machine learning life cycle (training data, fine-tuning, model operations)

Enterprise AI vendor vs build governance, compliance, and data sovereignty

Board-level AI transformation, generative risk, and competitive differentiation

Fine-tuning vs in-context learning, function calling, agentic loops, and multi-modal models

Cloud AI managed endpoints vs self-hosted Kubernetes GPU clusters

AI-assisted code reviews, automated test suite generation, and CI failure triage

TinyML on microcontrollers, edge sensor anomaly inference, and quantization

Inference runtime optimization (vendor-neutral), tool calling, and embeddings

Energy auditing for AI training vs inference, model quantization efficiency, and pruning

Go deeper

TPBOK Domain Guide 3 Applied AI, free in the IICTP library.

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Blog post

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