Amazon Web ServicesProfessionalAIP-C01
AWS Certified Generative AI Developer – Professional
Shows you can build production-grade generative AI applications on AWS: connecting models and data, keeping them safe, and testing and tuning them.
- Issuer
- Amazon Web Services
- Level
- Professional
- Exam code
- AIP-C01
- Exam format
- 75 questions · 180 minutes
- Focus
- Building generative AI apps
- Who it is for
- Developers and engineers who already build production applications and have worked with generative AI.
- Before you start
- AWS suggests 2 or more years building production-grade applications on AWS or with open-source tools, general AI/ML or data engineering experience, and 1 year of hands-on generative AI work.
What the exam covers
Listed as the issuer lists them, with weights where the issuer publishes them.
- Foundation model integration, data management and compliance (31%)
- Implementation and integration (26%)
- AI safety, security and governance (20%)
- Operational efficiency and optimization for GenAI applications (12%)
- Testing, validation and troubleshooting (11%)
Key terms to know
Words from this certification's topic areas, in plain English. Know these and the study material will be much easier to follow.
- Foundation model
- A large model trained on broad data that can be adapted to many tasks.
- Retrieval-augmented generation (RAG)
- Looking up relevant documents first, then giving them to the model to answer from.
- Embedding
- A list of numbers that captures the meaning of text, so similar meanings end up close together.
- Vector database
- A database that finds items by how similar their meaning is.
- Chunking
- Splitting documents into small pieces so they can be searched.
- Tool calling
- A model asking your code to run a function, such as a search or a database lookup.
- Model Context Protocol (MCP)
- A shared standard for connecting AI apps to tools and data.
- Guardrails
- Rules and filters that block unsafe inputs or outputs.
- Prompt injection
- Hidden instructions inside input that try to take control of the model.
- Evaluation (evals)
- Tests that measure how good a model or an AI app is.
- Latency
- How long a response takes to arrive.
- Amazon Bedrock
- An AWS service for using foundation models through an API.
Build the knowledge here
Our lessons are not exam prep for this certification, but they cover the same ground.
Details last checked Oct 7, 2026 against the issuer's own pages. Exams, versions and rules change. Confirm on the official page before you book. We are not affiliated with Amazon Web Services.