AIP-C01
AWS Certified Generative AI Developer - Professional
AIP-C01 - design and build production GenAI applications on AWS
Issued by Amazon Web Services
Visit official certification page
5
Domains
10+
Skills
3
Prep Links
1
Practice Quiz
Cost
$300 USD
Duration
180 minutes
Questions
75 total (65 scored + 10 unscored)
Pass
750 / 1000 (scaled)
Delivery
Pearson VUE test center OR OnVUE online proctored
Validity
3 years
Quick Facts
Cost
$300 USD
Duration
180 minutes
Questions
75 total (65 scored + 10 unscored)
Passing score
750 / 1000 (scaled)
Languages
English, Japanese, Korean, Simplified Chinese
Delivery
Pearson VUE test center OR OnVUE online proctored
Validity
3 years
Retake wait
14 days (standard AWS policy)
Skills You'll Learn
Design production-grade generative AI applications using foundation models on AWS.
Integrate vector stores, RAG, and Bedrock Knowledge Bases into apps.
Build agentic AI solutions using Amazon Bedrock AgentCore and multi-step reasoning.
Apply prompt engineering at scale - prompt management, versioning, evaluation.
Implement AI safety, security, governance including Bedrock Guardrails and content filtering.
Evaluate foundation models for quality, latency, cost, and responsibility trade-offs.
Optimize GenAI applications for cost, performance, and business value.
Troubleshoot, monitor, validate GenAI applications in production.
Apply development best practices (IaC, CI/CD, observability) to GenAI workloads.
Earn AWS's first Professional-level certification focused exclusively on generative AI.
Exam Logistics
- AWS's first Professional-level certification focused on generative AI.
- Question types: multiple choice and multiple response.
- GA version refreshed from beta (Oct 2025 - Mar 2026) to include Amazon Bedrock AgentCore content.
- Related: AWS Certified Machine Learning Specialty retired March 31, 2026.
Prerequisites & Recommended Experience
- No formal prerequisites.
- Recommended: 2+ years building production-grade apps on AWS or open-source tech.
- Recommended: general AI/ML or data engineering experience.
- Recommended: 1 year hands-on implementing generative AI solutions.
- Suggested prior certs: AI Practitioner, SAA, ML Engineer Associate, Data Engineer Associate.
Exam Domains with Weights
Domain 1: Foundation Model Integration, Data Management, Compliance
31%
- Designing solutions using vector stores, RAG, knowledge bases.
- Integrating foundation models into applications and workflows.
- Data management for GenAI pipelines.
Domain 2: Implementation and Integration
26%
- Prompt engineering and prompt management at scale.
- Implementing agentic AI solutions (Amazon Bedrock AgentCore).
- Application integration patterns.
Domain 3: AI Safety, Security, and Governance
20%
- Security, governance, Responsible AI.
- Evaluating foundation models for quality and responsibility.
Domain 4: Operational Efficiency and Optimization for GenAI Applications
12%
- Optimizing GenAI applications for cost, performance, and business value.
- Operational practices and cost management.
Domain 5: Testing, Validation, and Troubleshooting
11%
- Troubleshooting, monitoring, optimizing GenAI applications.
- Evaluating model outputs and validation patterns.
Official Prep Resources
Test what you've learned
Take a free GoLearnQuiz practice test. Sign in to save your score.
Additional Helpful Details
- Out-of-scope: model development/training, advanced ML techniques, data/feature engineering.
- Designed for developers, not model researchers or data scientists.