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AI Practitioner (Applied)

For engineers who ship AI systems, not slide decks.

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Overview

A scenario-based credential for practitioners building with models, retrieval and agents in production. Every objective is assessed against a described system — diagnosing a failure from a trace, bounding a loop, binding an approval, computing cost per correct completion — rather than against recall of terminology.

Exam domains

The certification blueprint and the weight of each domain.

Models, Prompting and Context16%

Retrieval and Data Lifecycle11%

Agents and Reliable Integrations21%

Evaluation and Observability15%

Security, Privacy and Authority15%

Software Engineering and Operation12%

Problem Framing, Economics and Delivery10%

What you'll prove

Choose the cheapest lever that solves the problem

Localise a failure to a step from a trace

Bound an agent loop in time, money and progress

Compute what a system costs per outcome that worked

Official prep

AIAP Exam Prep Program

7 modules · 29 hours of guided preparation aligned to the exam blueprint.

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