AWSFoundational
AWS Certified AI Practitioner
Exam: AIF-C01
The AWS GenAI fundamentals cert — Bedrock, SageMaker, and responsible AI basics.
~1 mo prepPractice questions
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AI / ML Engineer Certification Roadmap
AI engineering today spans classical ML on a cloud platform and generative-AI app development. This roadmap walks you from a fundamentals cert to senior ML/GenAI engineering on your platform of choice, plus the cross-vendor GenAI certs that are quickly becoming resume-required.
5 phases · 18 certifications9–18 months
ML EngineerAI EngineerGenAI EngineerApplied ScientistMLOps Engineer
Filter by vendor
1
Phase 1 — AI / Cloud Foundations
Pick a fundamentals cert that matches the platform you'll deepen into.
After this phase: You can describe core ML/AI concepts and the AI services of your chosen cloud.
MicrosoftFundamentals
Microsoft Certified: Azure AI Fundamentals
Exam: AI-901
Beginner-friendly Azure AI cert covering Cognitive Services, OpenAI on Azure, and ML basics.
~1 mo prepPractice questions
GoogleFoundational
Google Cloud Generative AI Leader
Exam: GCP-GEN-AI
GCP's GenAI-leader cert — business-leaning intro to Vertex AI and Gemini.
~1 mo prepPractice questions
AnthropicFoundationalCross-vendor
Claude Certified Architect — Foundations
Exam: CCA-F
Vendor-issued cert for building with the Claude API. Useful regardless of cloud.
~1 mo prepPractice questions
2
Phase 2 — Data & Cloud Platform
ML on the cloud assumes you can wrangle the underlying data and infrastructure.
After this phase: You can operate the data and compute services your ML workloads run on.
AWSAssociate
AWS Certified Solutions Architect – Associate
Exam: SAA-C03
Strong AWS fluency makes the MLA-C01 specialty exam dramatically easier.
~3 mo prepPractice questions
MicrosoftAssociate
Microsoft Certified: Azure Administrator Associate
Exam: AZ-104
Optional for ML engineers, but useful if you'll own the underlying Azure infrastructure.
~3 mo prepPractice questions
MicrosoftFundamentals
Microsoft Certified: Azure Data Fundamentals
Exam: DP-900
Establishes the data vocabulary AI engineers need before AI-103 or AI-300.
~1 mo prepPractice questions
GoogleAssociate
Google Cloud Associate Cloud Engineer
Exam: GCP-ACE
Lays the GCP foundation that the Professional ML Engineer cert assumes.
~3 mo prepPractice questions
3
Phase 3 — ML Engineer Role
The cert that says you can ship ML on your platform.
After this phase: You can train, deploy, monitor, and govern ML models in production.
AWSAssociate
AWS Certified Machine Learning Engineer – Associate
Exam: MLA-C01
AWS's flagship ML engineer cert — heavy on SageMaker, feature stores, and MLOps.
~3 mo prepPractice questions
MicrosoftAssociate
Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate
Exam: AI-300
Azure's MLOps cert — Azure Machine Learning, Azure DevOps integration, model registries.
~3 mo prepPractice questions
GoogleProfessional
Google Professional Machine Learning Engineer
Exam: GCP-PMLE
The senior ML engineer cert on GCP — Vertex AI, pipelines, and TFX.
~4 mo prepPractice questions
DatabricksML Engineer
Databricks Certified Machine Learning Associate
Exam: MLA
If your stack runs on Databricks, this is the most relevant ML engineer cert in the market.
~3 mo prepPractice questions
4
Phase 4 — Generative AI Engineering
Production GenAI is a distinct skill: retrieval, agents, eval, and safety.
After this phase: You can build, evaluate, and operate GenAI apps with RAG, agents, and guardrails.
AWSProfessional
AWS Certified AI Practitioner Professional
Exam: AIP-C01
AWS's senior GenAI cert — Bedrock agents, knowledge bases, evaluation, and guardrails.
~3 mo prepPractice questions
MicrosoftAssociate
Microsoft Certified: Azure AI Apps and Agents Developer Associate
Exam: AI-103
Azure's GenAI developer cert — Azure OpenAI, agents, RAG, and Cognitive Search.
~2 mo prepPractice questions
DatabricksGenerative AI Engineer
Databricks Certified Generative AI Engineer Associate
Exam: GAIEA
Databricks' GenAI engineer cert — Vector Search, Model Serving, and RAG on Mosaic AI.
~2 mo prepPractice questions
GitHubAssociateCross-vendor
GitHub Agentic AI Developer
Exam: GH-600
GitHub's GenAI/agentic cert — useful regardless of cloud and aligned with how teams actually ship.
~2 mo prepPractice questions
5
Phase 5 — Specialize
Pick what aligns with your role — research engineer, MLOps lead, or AI architect.
After this phase: You bring a specialty alongside your core ML engineer credential.
AWSSpecialty
AWS Certified Machine Learning – Specialty
Exam: MLS-C01
The older AWS ML specialty — still useful if your job touches deeper algorithmic work.
~3 mo prepPractice questions
DatabricksML Engineer
Databricks Certified Machine Learning Professional
Exam: MLP
The senior Databricks ML cert. Assumes deep platform fluency.
~3 mo prepPractice questions
Frequently Asked Questions
Should I start with classical ML or GenAI?
Classical ML still pays best at the senior level, but GenAI is where new jobs are appearing fastest. Most engineers do both — start with the fundamentals cert that matches your day job.
Do I need a math/stats background for these certs?
The cloud ML engineer certs (MLA-C01, AI-300, PMLE) are engineering-heavy and light on theory. The Databricks specialty path is more algorithmic.
Related Roadmaps
🗃️
Data Engineer Certification Roadmap
Build a data engineering career on AWS, Azure, GCP, or Databricks — with the cross-vendor data skills senior roles require.
🏛️
Cloud Architect Certification Roadmap
Become a cloud solutions architect on AWS, Azure, or GCP — with the cross-cloud and platform skills that get you to senior.