AIP-C01

AWS Certified Generative AI Developer - Professional

Prepare for the AIP-C01 exam and master integrating foundation models into applications using Amazon Bedrock, RAG architectures, prompt engineering, and responsible AI practices.

80 lessons
16 hours
5 modules
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Course Content

5 modules · 80 lessons

Module 1: Foundation Model Integration and Data Management

Design GenAI solutions, select FMs, implement data pipelines, and configure vector stores. (31% of exam)

GenAI Solution Design

Analyze requirements and design comprehensive GenAI architectures.

Foundation Model Selection

Select and configure foundation models for specific use cases.

Data Validation and Processing

Implement data pipelines for FM consumption.

Vector Store Solutions

Design and implement vector databases for semantic search.

Retrieval Mechanisms

Design retrieval systems for FM augmentation.

Prompt Engineering

Implement prompt strategies and governance.

Module 2: Implementation and Integration

Implement agentic AI, model deployment, and enterprise integrations. (26% of exam)

Agentic AI Solutions

Develop intelligent autonomous systems with tool integrations.

Model Deployment

Deploy FMs for production workloads.

Enterprise Integration

Integrate GenAI into enterprise environments.

FM API Integration

Implement FM API interactions.

Application Development

Build GenAI applications with AWS tools.

Module 3: AI Safety, Security, and Governance

Implement safety controls, data security, and responsible AI. (20% of exam)

Input and Output Safety

Implement content safety and output validation.

Data Security and Privacy

Protect sensitive data in GenAI applications.

Governance and Compliance

Implement governance for GenAI deployments.

Responsible AI

Apply responsible AI principles.

Module 4: Operational Efficiency and Optimization

Optimize cost, performance, and monitoring for GenAI. (12% of exam)

Cost Optimization

Implement cost-effective GenAI strategies.

Performance Optimization

Optimize GenAI application performance.

Monitoring and Observability

Monitor GenAI applications in production.

Module 5: Testing, Validation, and Troubleshooting

Evaluate, test, and troubleshoot GenAI applications. (11% of exam)

GenAI Evaluation

Evaluate FM outputs and quality.

Testing Strategies

Test GenAI applications effectively.

Troubleshooting

Diagnose and resolve GenAI issues.

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