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Category - Artificial Intelligence & Machine Learning

AI and ML certifications for the technology reshaping every industry

Microsoft Azure dominates enterprise AI deployment. AI-900 is the fastest entry point. AI-102 is for engineers who build and deploy AI solutions. Both are growing faster than any other certification category.

2
Certs covered
$148k
Top cert salary (AI-102)
85%
AI-900 pass rate
Compare all certifications 
Certification
pass rate
Difficulty
Prep time
Exam cost
Salary uplift
Best for
Readiness Test for
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Azure AI Engineer AI-102 ★ Top pick
Microsoft
70%
8 w $165 +41% AI solution builders on Azure Check AI-102 Readiness Explore →
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Azure AI Fundamentals AI-900
Microsoft
85%
3 w $165 +38% AI fundamentals for non-technical professionals Check AI-900 Readiness Explore →
Career path sequences 
Developer AI Engineer
Building and deploying AI solutions on Azure. Fastest-growing role.
AI-900 → AI-102
⏱ 1–2 year path · $148k+ potential
Salary impact by certification 
Median salary before vs after certification - US market
Azure AI Engineer AI-102
$105k
$148k
+41%
Azure AI Fundamentals AI-900
$52k
$72k
+38%
Is this category right for your goals? 
✅ You should certify in AI/ML if…
You're a developer wanting to add AI capabilities to your applications
You work in cloud architecture and want to specialise in AI workloads
Your organisation is deploying AI solutions on Azure
You want to move from data analytics into AI engineering
⚠️ Consider alternatives if…
You have no programming background - AI-900 is accessible, but AI-102 requires development skills
You're targeting data science rather than AI engineering - consider Google Professional ML Engineer
You want vendor-neutral AI credentials - AWS and Google also offer competitive AI certifications not yet covered here
Explore our top-rated prep 
Frequently asked questions 
Azure AI Engineer Associate (AI-102) certifies professionals who design and implement AI solutions using Azure Cognitive Services, Azure Machine Learning, Azure Bot Service, and related AI tools. It requires programming skills (typically Python or C#) and experience with Azure. It is most valuable for developers and solution architects building AI-powered applications in Microsoft Azure environments.
AI-900 (Azure AI Fundamentals) requires no programming background and covers AI concepts, machine learning, computer vision, NLP, and Azure AI services at a high level. It is appropriate for non-technical professionals, business stakeholders, or developers completely new to AI. AI-102 requires programming skills and is for practitioners who will actually build AI solutions. If you are a developer with Azure experience, go directly to AI-102. If you're non-technical, start with AI-900.
Both are strong credentials, but they target different ecosystems. Azure AI-102 is most valuable in Microsoft Azure environments and enterprise settings where Azure is the primary cloud. Google Professional ML Engineer is stronger for ML-focused roles, data science pipelines, and organisations using GCP. If your organisation is Azure-first, AI-102 is the clear choice. If you're in a cloud-agnostic or GCP environment, Google's ML Engineer certification may be more valuable.

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