Exam prep for
AWS Certified Generative AI Developer – Professional
Exam set and awarded by Amazon Web Services On demand AIP-C01
For experienced AWS and generative AI developers: prepare for the AWS Certified Generative AI Developer – Professional credential while strengthening your ability to build, secure, optimize, and validate production generative AI applications.
Included with Elandi Pro: practice on all 5 exam domains and unlimited mock exams.
Independent exam prep. Elandi is not affiliated with, endorsed by or approved by Amazon Web Services, and does not award Amazon Web Services credentials. Our practice questions and mocks are written by Elandi, not taken from the real exam. Exam names are trademarks of their owners. AWS, Amazon Web Services and all related certification names are trademarks of Amazon.com, Inc. or its affiliates.
The exam in numbers
Assesses the integration of foundation models into applications and business workflows and the implementation of production generative AI solutions using AWS technologies. Questions use multiple choice and multiple response formats. Your mock exams use this learning plan's question count, time limit and pass mark.
- Questions
- 75
- Time limit
- 180min
- Mock pass mark
- 75%
- 57 correct
- Exam fee (paid to Amazon Web Services)
- US$300
- When you book the exam
- Sitting
- On demand
- Single select (Radio): 4 options
- Multiple select (Checkbox): 5 options
Upcoming sittings
Pick a sitting when you start. Your workspace counts down to it and paces your prep from there.
- Any day On demand Book any day
What AWS Certified Generative AI Developer – Professional covers
5 modules · 20 units · ~20h of structured prep. Each exam domain with the weight the exam gives it, and the modules that prepare you for it.
- 01Foundation Model Integration, Data Management, and Compliance 31%
- Analyze requirements and design GenAI solutions
- Select and configure FMs
- Implement data validation and processing pipelines for FM consumption
- Design and implement vector store solutions
- Design retrieval mechanisms for FM augmentation
- Implement prompt engineering strategies and governance for FM interactions
- 02Implementation and Integration 26%
- Implement agentic AI solutions and tool integrations
- Implement model deployment strategies
- Design and implement enterprise integration architectures
- Implement FM API integrations
- Implement application integration patterns and development tools
- 03AI Safety, Security, and Governance 20%
- Implement input and output safety controls
- Implement data security and privacy controls
- Implement AI governance and compliance mechanisms
- Implement responsible AI principles
- 04Operational Efficiency and Optimization for GenAI Applications 12%
- Implement cost optimization and resource efficiency strategies
- Optimize application performance
- Implement monitoring systems for GenAI applications
- 05Testing, Validation, and Troubleshooting 11%
- Implement evaluation systems for GenAI
- Troubleshoot GenAI applications
Your exam workspace counts down and keeps score
Set your exam day once. The workspace paces your prep in four phases, weighs your coverage by what each topic is worth, and shows where the marks are still open after every mock.
- Overview
- All attempts
- Review
- Preview questions
- Questions
- 75
- Time limit
- 180 minutes
- Pass score
- 75% · 57 correct
days until your exam
6 weeks
Thursday, 24 December 2026
- Learn 8+ weeks out
- Mock and repair 8 to 2 weeks out
- Simulate Last 2 weeks
- Consolidate Last 3 days
Now: Mock and repair. Sit a full mock every week or two, then practise the topics you missed.
How ready you are
- Exam-weighted coverage
- 81% of the plan, counted by what each topic is worth
- Full mocks taken
- 2 Prep guides suggest three to five before the exam
- Latest mock
- 71% 4 points below the 75% pass mark
Where the marks are still open
- AI Safety, Security, and Governance 20% of the exam 71%
- Operational Efficiency and Optimization for GenAI Applications 12% of the exam 54%
- Testing, Validation, and Troubleshooting 11% of the exam 63%
- Foundation Model Integration, Data Management, and Compliance 31% of the exam 88%
- Implementation and Integration 26% of the exam 100%
How the content is written
Write for experienced production developers preparing to apply generative AI on AWS in professional exam scenarios. Emphasize defensible implementation choices, operational constraints and trade-offs.
- Worked examples
- Heavy
- Technical jargon
- Heavy
- Maths & formulas
- Light
- Code
- Light
- Diagrams
- Light
Try a sample question
Elandi wrote these in this learning plan's style. Pick an answer to see whether it's right and why. They are not taken from the exam.
An enterprise assistant must retrieve from a supported SharePoint connector and enforce document-level permissions at retrieval. The small application team wants to minimize ownership of ingestion, indexing, storage and retrieval infrastructure. Which design best meets these constraints? One answer
A RAG assistant must reduce unsupported answers without obscuring why failures occur. The team has representative queries with known current evidence and must preserve an auditable path for diagnosing both retrieval and generation. Which TWO actions best address the requirement? (Select TWO.) Select all that apply
A production RAG application sends a system instruction, retrieved passages and a user question to a supported Amazon Bedrock model. A tested guardrail must screen the user question for a denied topic, but must not reject a request merely because the same topic is discussed in the retrieved passages or system instruction. The approved configuration must be stable across deployments. Which approach best meets these requirements? One answer
A production assistant on Amazon Bedrock is over its inference budget. The team must reduce cost while meeting an existing answer-quality threshold and a tail-latency objective; its evaluation set includes representative difficult queries. Which TWO actions form the most defensible optimization process? (Select TWO.) Select all that apply
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