- Certification Path Libraries: This path is only available in the libraries listed. To access this path, purchase a license for the corresponding library.
- Cloud
AWS Certified Generative AI Developer - Professional (AIP-C01)
The **AWS Certified Generative AI Developer - Professional (AIP-C01)** certification validates advanced technical skills in designing, building, and deploying production-ready generative AI solutions on AWS. This path prepares learners to integrate foundation models, build RAG architectures, work with vector databases, and implement responsible AI practices using services like Amazon Bedrock.
This learning path is actively in production. More content will be added to this page as it gets published and becomes available in the library. Planned content includes:
- AIP-C01: Foundation Model Integration, Data Management, and Compliance - AIP-C01: Implementation and Integration - AIP-C01: AI Safety, Security, and Governance - AIP-C01: Operational Efficiency and Optimization for GenAI Applications - AIP-C01: Testing, Validation, and Troubleshooting - Exam Strategy and Prep for AWS Certified Generative AI Developer - Professional (AIP-C01)
Content in this path
Path courses for AWS Certified Generative AI Developer - Professional (AIP-C01)
Watch the following courses to get learning about generative AI development on AWS and prepare for the AIP-C01 certification exam!
Try this certification path for free
Build confidence to ace your certification exam with a variety of prep tools, including video courses, labs, and practice exams.
What You'll Learn
- How to integrate foundation models (FMs) into applications and business workflows
- How to design and implement solutions using vector stores, Retrieval Augmented Generation (RAG), and knowledge bases
- How to select and configure foundation models based on business use cases and technical requirements
- How to manage data pipelines and ensure compliance for generative AI workloads
- How to implement AI safety, security, and governance best practices on AWS
- How to optimize generative AI applications for operational efficiency and cost
- How to test, validate, and troubleshoot production generative AI systems
- Candidates should have at least two years of hands-on experience building production-grade applications on AWS and at least one year of practical experience implementing generative AI solutions. AWS recommends familiarity with core AWS services (compute, storage, networking, and security), AWS deployment and infrastructure as code (IaC) tools, and a foundational understanding of AI/ML concepts — ideally demonstrated through the AWS Certified AI Practitioner (AIF-C01) or AWS Certified Machine Learning Engineer Associate (MLA-C01).
- Generative AI
- Foundation Models
- RAG
- Machine Learning
- LLM
- AWS
- AI
- Prompt Engineering
- Responsible AI
Learn with the best
