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SHAJAM
SHAJAM

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Yet Another AWS AI Certification - AI Professional

#aws #certification

Introduction

Generative AI is rapidly becoming a business-critical capability. AWS launched a new specialised certification for AI domain as per AI certification. The certification is currently in beta stage.

Note, AWS is also decommissioning the Machine Learning Specialty certification.

What the certification is & who it's for

  • The AWS Certified Generative AI Developer – Professional is a Professional-level certification.
  • It is currently in beta (as of the announcement) – registration opens November 18 2025.
  • Exam overview: 204 minutes, ~85 questions (multiple choice / multiple response). - more questions than usual
  • Target candidate: developers with 2+ years of cloud experience, plus 1 year of hands-on experience implementing generative AI solutions. Also experience with AWS compute/storage/networking, security, deployment/infrastructure-as-code, monitoring/observability, cost optimisation.
  • It is aimed at those who are beyond proof-of-concept and can build and deploy production-ready generative AI solutions using AWS services (such as AWS Bedrock) and open-source tools.

Core knowledge & skills validated

You might emphasise what a "generative AI developer" in AWS world needs to know. From the AWS page we have hints; you'd likely want to infer/expand:

  • Understanding the AWS services and infrastructure for generative AI (e.g., AWS Bedrock, compute/storage/networking, identity/security).
  • Ability to design and implement generative AI models/solutions: selecting appropriate foundation models or open-source models, fine-tuning or customising them, integrating them with applications.
  • Deployment and operationalisation: infrastructure-as-code, cost optimisation, monitoring/observability, maintenance of models in production.
  • Security, governance, and responsible AI: managing identity and access, data privacy, model risk, bias mitigation.
  • Business value: building solutions that deliver measurable results, not just experiments. Identifying metrics, aligning with organisational goals, cost vs benefit.
  • Possibly multi-modal/advanced use-cases: text generation, image/video/audio, prompt engineering, RAG, pipelines, evaluation and iteration.

How to prepare (and prerequisites)

  • While no prior AWS certification is required, AWS suggests it might help to have other certifications such as: AWS Certified AI Practitioner, AWS Certified Solutions Architect – Associate, AWS Certified Machine Learning Engineer – Associate, AWS Certified Data Engineer – Associate.

  • Recommended to have hands-on experience: 2+ years with cloud and at least 1 year with generative AI solutions.

  • Preparation tips:

    • Get hands-on with AWS generative AI services (e.g., AWS Bedrock, SageMaker JumpStart, etc)
    • Study deployment/infrastructure aspects: network, security, observability, cost control
    • Study model integration: prompt engineering, retrieval-augmented generation (RAG), evaluation metrics for generative output.
    • Work through case studies: how generative AI is applied in businesses (content creation, summarisation, code generation, image/video generation, multimodal assistants)
    • Use Official AWS resources: exam guides, sample questions, training courses, labs.
    • Simulate environments: build a prototype end-to-end solution in AWS from data ingestion → model integration → production deployment → monitoring.

  • Mention that because it's a beta exam, early takers will be among the first to hold the certification.

Potential caveats / things to note

  • As with any certification: passing the exam doesn't automatically make you expert — practical experience still matters.
  • Being AWS-specific: It is focused on AWS services. So if you are working on other clouds/platforms you may still need to master those.
  • Because it's a beta exam, details may change as AWS finalises the content and certification.
  • The pace of generative AI is fast — new techniques emerge quickly — so continuous learning beyond the certification will be key.

Conclusion

The AWS Certified Generative AI Developer – Professional certification gives developers and organisations a structured way to validate generative-AI development expertise on AWS. It reflects the maturity of the generative-AI domain moving into production, and offers a pathway for career growth and organisational readiness.
For those looking to build generative AI solutions in the cloud, it's a timely credential to consider.

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