AWS
For teams using Bedrock, SageMaker, Glue and AWS infrastructure. AI Practitioner is a foundation; Generative AI Developer is an advanced implementation path.
AI CERTIFICATION PATHWAYSAI certifications.
AI certifications.
Matched to your experience.
AI literacy, application development, production ML and business leadership are different skills. Choose the path that fits the work you want to do.
Official sources checked 13 September 202601
FOUNDATIONS · 0–1 YEAR
Start with AI
Understand what AI can do, where it helps and the basics of working with it. Choose a technical or a business foundation.
Personalise this pathPut it into practiceTry a small AI use case and record where its answers work, fail or need a human check.
02
PRACTITIONERS · 1–3 YEARS
Build AI applications
Turn programming and platform skills into useful applications. Focus on agents, retrieval, integrations and evaluation.
Personalise this pathPut it into practiceBuild an assistant with reliable retrieval, citations, access controls and a test set to measure answer quality.
03
EXPERIENCED PRACTITIONERS · 3+ YEARS
Operate & specialise
Build on real delivery experience. Show that you can deploy, secure, evaluate and improve production AI and ML systems.
Personalise this pathPut it into practiceDeploy a production-style AI service with monitoring, safety evaluations, cost controls and rollback.
04
BUSINESS, PRODUCT & PROGRAMME LEADERS
Lead AI adoption
Choose this path if you guide investment, transformation or governance. Coding is not the focus; business context and responsible decisions are.
Personalise this pathPut it into practiceCreate an AI business case with success metrics, governance, stakeholder responsibilities and a staged adoption plan.
Follow the work, then the cloud.
Microsoft
For Azure and Foundry builders, Fabric teams or organisations using Copilot. AB-730 and AB-731 focus on business work; AI-103 and AI-200 focus on development.
Google Cloud
For Vertex AI, BigQuery and Google Cloud environments. Generative AI Leader suits business understanding; Professional ML Engineer fits experienced technical work.
Databricks and Snowflake can complement more than one cloud. You do not need to collect all three cloud providers’ certifications. Check the technology used in your current team and target roles first.
Make it your own.
Compare certifications by role, platform and experience, then save the options that matter.
Open the AI certification finder