AWS's Certified Generative AI Developer – Professional (AIP-C01) is the vendor's bid to standardize production-grade GenAI integration on AWS — not model training research, but the practical work of shipping Bedrock-powered apps with RAG, agents, guardrails, and cost controls.
This post is a field guide: format, domains, scenario framing, pricing, official prep, and how explainx.ai fits in — including timed mock tests, a certification study guide, and a structured learning pathway.
Disclaimer: Exam structure and policies belong to AWS and Pearson VUE. Confirm details on the official certification page and AWS Skill Builder exam prep before you register.
Who it is for
AWS positions the target candidate as someone with 2+ years building production-grade applications on AWS (or equivalent open-source experience), plus 1 year hands-on implementing GenAI solutions.
You should be comfortable with:
- AWS compute, storage, and networking
- IAM, VPC security, and cost optimization fundamentals
- Integrating Amazon Bedrock, Knowledge Bases, Guardrails, and orchestration services
Explicitly out of scope: model training from scratch, advanced ML research, and data engineering unrelated to FM consumption.
Exam format (at a glance)
| Attribute | Detail |
|---|---|
| Duration | 180 minutes |
| Questions | 75 total — 65 scored + 10 unscored (unscored items are not identified on the exam) |
| Format | Multiple choice and multiple response (select all correct answers) |
| Proctoring | Pearson VUE testing center or online proctored |
| Pass score | 750 / 1000 scaled (compensatory — pass overall, not per domain) |
| Pricing | $300 USD per attempt |
| Languages | English, Japanese, Korean, Simplified Chinese |
What you are tested on: five competency areas
| Area | Weight | What it emphasizes |
|---|---|---|
| Foundation Model Integration, Data Management, and Compliance | 31% | FM selection, RAG/vector stores, Knowledge Bases, chunking, embeddings, prompt governance |
| Implementation and Integration | 26% | Bedrock Agents, Step Functions, MCP, API Gateway, enterprise GenAI gateway, CI/CD |
| AI Safety, Security, and Governance | 20% | Guardrails, PII, IAM/VPC, compliance, responsible AI, hallucination reduction |
| Operational Efficiency and Optimization | 12% | Token efficiency, caching, model routing, CloudWatch observability |
| Testing, Validation, and Troubleshooting | 11% | Model evaluation, RAG quality testing, agent performance, GenAI-specific debugging |
Domain 1 alone is nearly a third of the exam — RAG architecture and data pipelines deserve the most study time, followed by agents and enterprise integration.
Production scenarios (six frames for practice)
explainx practice questions are scenario-framed around realistic AWS GenAI workloads:
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Enterprise Knowledge Assistant (RAG) — Bedrock Knowledge Bases, OpenSearch hybrid search, Titan embeddings, incremental index sync.
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Bedrock Agent & Tool Orchestration — Strands Agents, Step Functions ReAct, Lambda MCP servers, circuit breakers.
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Regulated Data & Responsible AI — Guardrails, Comprehend/Macie PII, VPC endpoints, CloudTrail audit trails.
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Multimodal Document Processing — Transcribe, SageMaker Processing, Glue Data Quality, Bedrock multimodal models.
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Cost-Optimized GenAI at Scale — Semantic caching, tiered model routing, provisioned throughput planning.
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Enterprise GenAI Gateway & CI/CD — API Gateway abstraction layers, EventBridge, CodePipeline, identity federation.
Full task-level detail lives in the official AIP-C01 Exam Guide.
Practice exam
AWS Certified Generative AI Developer - Professional — Mock Tests
3 timed mock exams with shuffled questions, instant scoring, and per-question explanations. Pass score: 720/1000. The fastest way to find your weak domains before exam day.
Official resources
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AWS Certification landing page — exam overview, scheduling, and policies.
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AWS Skill Builder — AIP-C01 Exam Prep — official practice questions, digital courses, and the four-step prep plan.
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Recommended prior credentials (not required): AWS Certified AI Practitioner, Solutions Architect Associate, Machine Learning Engineer Associate, or Data Engineer Associate.
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Related microcredential: AWS Agentic AI Demonstrated — practical implementation skills that complement the Professional exam.
How explainx.ai fits: mock tests and study pathway
AWS GenAI Developer mock tests — live on explainx.ai
Start mock tests → — eight timed practice exams (Foundations drills, RAG focus, agents focus, security focus, cost/monitoring focus, scenario marathon, 65-question / 180-minute simulation), 1,000+ shuffled multiple-choice questions, instant explanations, $5 lifetime access.
Certification study guide → — domain weights, task statements per competency area, six scenario narratives, in-scope / out-of-scope topics, and AWS service checklist mapped to the official Exam Guide.
Learning pathway → — 18 articles mapped to exam domains with embedded quiz questions.
Related on explainx.ai
- AWS GenAI Developer mock tests — timed practice exams
- Certification study guide — domains, scenarios, task map
- Embeddings & vector search guide — RAG foundations
- RAG pipeline design — chunking and retrieval
- Multi-agent orchestration — Step Functions and agent patterns
- Prompt caching & cost optimization — token efficiency
Bottom line
AWS Certified Generative AI Developer – Professional validates that you can move beyond POC to production GenAI on AWS — RAG, agents, security, cost, and evaluation. Start from the official Exam Guide and Skill Builder prep plan, follow the explainx pathway, and run mock tests for timed MCQ practice before your Pearson VUE sitting.
Practice exam
AWS Certified Generative AI Developer - Professional — Mock Tests
3 timed mock exams with shuffled questions, instant scoring, and per-question explanations. Pass score: 720/1000. The fastest way to find your weak domains before exam day.
Exam names, weights, and policies are summarized from AWS's public certification messaging; verify on AWS before registering. explainx.ai is not affiliated with AWS's certification program.