AWS GenAI Professional AIP-C01 Practice Exams | 2026

Prepare with Confidence for the AWS Certified Generative AI Developer – Professional (AIP-C01) Certification

Preparing for the AWS Certified Generative AI Developer – Professional (AIP-C01) exam?

These realistic AWS AIP-C01 Practice Exams are designed to simulate the real certification experience and help you confidently pass the exam on your first attempt.

Practice with 350+ high-quality, scenario-based questions covering Amazon Bedrock, Prompt Engineering, Retrieval-Augmented Generation (RAG), Guardrails, Agents, Knowledge Bases, Foundation Models, Security, Responsible AI, LLMOps, MLOps, and every domain of the official AWS exam blueprint.

Whether you're validating your knowledge after completing AWS Skill Builder, preparing after instructor-led training, or getting ready for your certification exam, these practice exams are designed to identify knowledge gaps and strengthen your decision-making skills.

Why Students Love These Practice Exams

5 STARS

"These questions are excellent and require careful brainstorming. Each presents a unique challenge, closely reflecting the style and difficulty of the original examination, and it's easy to be distracted by other answer choices."

5 STARS

"Questions are well worded and mimic what you will encounter in the real exam."

5 STARS

"Very good question to practice the course subject and have strong knowledge about concepts and i have gained good confidence on me to give best at exam."

5 STARS

"I feel the questions are a good point to reference for how the exam may test you"

What Makes This Course Different?

Realistic Exam-Level Questions

Every question is carefully crafted to reflect the style, complexity, and decision-making required in the actual AWS Certified Generative AI Developer – Professional (AIP-C01) certification exam.

You'll practice solving real-world scenarios instead of memorizing facts.

Detailed Explanations for Every Answer

Every question includes comprehensive explanations that explain:

• Why the correct answer is correct

• Why every incorrect option is incorrect

• The AWS services involved

• The architectural reasoning behind the solution

The objective is to help you truly understand AWS Generative AI services—not simply memorize answers.

Covers Every Official AIP-C01 Exam Domain

These practice exams comprehensively cover all domains of the official AWS exam blueprint, including:

• Designing Generative AI Solutions

• Prompt Engineering

• Foundation Models

• Model Selection

• Model Evaluation

• Retrieval-Augmented Generation (RAG)

• Embeddings

• Vector Databases

• Amazon Bedrock

• Amazon Bedrock Knowledge Bases

• Amazon Bedrock Guardrails

• Amazon Bedrock Agents

• Amazon Bedrock Flows

• Prompt Routers

• Amazon Nova Models

• Amazon Titan Models

• Third-party Foundation Models

• SageMaker AI

• Data Engineering

• LLMOps

• MLOps

• Responsible AI

• AI Governance

• Security

• Identity and Access Management (IAM)

• Encryption

• Cost Optimization

• Monitoring

• Deployment

• Performance Optimization

Designed to Build Real Problem-Solving Skills

The certification exam measures your ability to analyze scenarios—not memorize documentation.

These practice exams train you to:

• Analyze long AWS certification questions

• Identify subtle differences between similar services

• Select the most operationally efficient solution

• Design secure AI architectures

• Reduce hallucinations

• Apply Guardrails correctly

• Build Retrieval-Augmented Generation (RAG) architectures

• Optimize cost and performance

• Apply AWS security best practices

• Think like an AWS Solutions Architect and Generative AI Developer

Continuously Updated

AWS Generative AI evolves rapidly.

This course is regularly updated to reflect the latest AWS services, features, and certification objectives, ensuring your preparation stays aligned with the current AIP-C01 exam blueprint.

New questions are added as AWS introduces new capabilities and best practices.

What You'll Practice

These practice exams include questions on topics such as:

• Amazon Bedrock

• Amazon Bedrock Agents

• Amazon Bedrock Guardrails

• Amazon Bedrock Knowledge Bases

• Amazon Bedrock Flows

• Prompt Engineering

• Prompt Templates

• Prompt Routers

• Foundation Models

• Amazon Nova

• Amazon Titan

• Anthropic Claude

• Embeddings

• Vector Databases

• Retrieval-Augmented Generation (RAG)

• AI Evaluation

• Model Customization

• Fine-Tuning Concepts

• Responsible AI

• AI Governance

• Security

• IAM Policies

• Encryption

• Networking

• Monitoring

• Logging

• Performance Optimization

• Cost Optimization

• SageMaker AI

• LLMOps

• MLOps

SAMPLE QUESTION + SOLUTION EXPLANATION

A company is implementing AI governance policies. The policies require all FM interactions to be secured with guardrails. The company configures Amazon Bedrock guardrails. The company must ensure that all InvokeModel and Converse API calls to FMs apply the guardrails.

Which solution will enforce guardrail compliance for the API calls in the MOST operationally efficient way?

A. Configure IAM policies for the InvokeModel and Converse API calls with both bedrock:GuardrailIdentifier and bedrock:PromptRouterArn condition keys. Apply the policies to all IAM roles. Require prompt router validation before allowing access to Amazon Bedrock FMs.

B. Create an AWS Lambda function that validates and enforces guardrails before proxying requests to Amazon Bedrock. Use the Lambda function as the exclusive endpoint for all FM interactions.

C. Store guardrail identifiers in AWS Systems Manager Parameter Store. Create an AWS Lambda function that retrieves the guardrail identifier from Parameter Store each time before making calls to Amazon Bedrock FMs.

D. Configure IAM policies for the InvokeModel and Converse API calls with the bedrock:GuardrailIdentifier condition key. Apply the policies to all IAM roles that access the Amazon Bedrock FMs.

Explanation:

The correct answer is : D

This solution uses IAM policies with the bedrock:GuardrailIdentifier condition key to enforce guardrail compliance for InvokeModel and Converse API calls. IAM policies are a centralized and efficient way to control access to AWS resources. You can apply the policies to roles that access Amazon Bedrock FMs. This solution ensures that guardrails are consistently applied across all relevant API calls in the most operationally efficient way.

The other Options :

A : Incorrect. The PromptRouterArn condition key is designed to filter access by the specified prompt router. The prompt router manages prompt templates and configurations. This condition key is unrelated to guardrail enforcement. Using both conditions creates more complex IAM policies to maintain without providing additional security benefits.

B : Incorrect. Creating a Lambda function to proxy and validate all requests introduces an additional point of failure and a potential performance bottleneck. You must maintain custom code for guardrail enforcement. Therefore, this solution is less operationally efficient and more error-prone than using built-in capabilities.

C : Incorrect. Parameter Store provides a centralized location to store guardrail identifiers. However, using a Lambda function to retrieve the identifier for each API call adds additional operational overhead and latency. You must create and maintain the Lambda function. This solution requires the retrieval of the guardrail identifier each time before making a call to the model.