Applied AI · 6 priority credentials
Applied AI certifications, organized by level.
DecipherU covers six priority Applied AI certifications across three tiers. Foundation credentials build vocabulary. Practitioner credentials validate production readiness on AWS, Azure, or Google Cloud. Governance credentials cover AI law, policy, and program design. Each cert has its own deep-dive guide with cost, format, study hours, and the roles it supports.
Foundation (2)
Foundation tier. Vocabulary, vendor-agnostic AI literacy, and the conceptual ground needed before crossing into practitioner work. Under 100 dollars in most cases. About 25 to 30 hours of prep.
AWS Certified AI Practitioner
$100 examAmazon Web Services · 30h prep
Fundamentals of AI, machine learning, and generative AI on AWS
Read the AWS Certified AI Practitioner guide →
Microsoft Certified: Azure AI Fundamentals
$99 examMicrosoft · 25h prep
Fundamentals of artificial intelligence, machine learning, and generative AI
Read the Microsoft Certified: Azure AI Fundamentals guide →
Practitioner (3)
Practitioner tier. Production engineering on the relevant cloud platform. Validates readiness to ship AI features under cost, latency, and reliability constraints. 60 to 100 hours of prep.
AWS Certified Machine Learning Engineer Associate
$150 examAmazon Web Services · 80h prep
Data preparation, feature engineering, and data quality on AWS
Read the AWS Certified Machine Learning Engineer Associate guide →
Microsoft Certified: Azure AI Engineer Associate
$165 examMicrosoft · 60h prep
Azure AI Services across vision, language, speech, decision, and document intelligence
Read the Microsoft Certified: Azure AI Engineer Associate guide →
Google Cloud Professional Machine Learning Engineer
$200 examGoogle Cloud · 100h prep
Architecting low-code AI solutions and building ML pipelines on Vertex AI
Read the Google Cloud Professional Machine Learning Engineer guide →
Governance (1)
Governance tier. AI law, policy, risk frameworks, and program design. The credential serious privacy and compliance professionals add when the organization shifts AI governance from advisory to operational.
Applied AI certification questions and answers
Which Applied AI certification should I start with?
Start with a foundation-tier credential matched to your cloud platform. AWS-first organizations: AWS Certified AI Practitioner. Microsoft-first organizations: Azure AI Fundamentals. Both run under $100, take about 25 to 30 hours to prep, and give the AI vocabulary needed before crossing into practitioner-tier work.
Are Applied AI certifications worth it for a job search?
Yes for the practitioner-tier credentials when paired with a portfolio. AWS ML Engineer Associate, Azure AI Engineer Associate, and Google Cloud Professional ML Engineer all signal production readiness on the relevant cloud. Foundation-tier certs help with vocabulary and confidence but rarely move a hiring decision on their own.
What is the AIGP and who is it for?
The IAPP Artificial Intelligence Governance Professional (AIGP) is a governance-tier credential covering AI law, policy, and program design. It targets privacy professionals, lawyers, risk managers, and AI governance leads who need fluency in the EU AI Act, NIST AI RMF, and ISO 42001 to operationalize AI governance programs.
How do AWS, Azure, and Google Cloud Applied AI certs compare?
All three practitioner-tier credentials cover the same conceptual ground (data prep, training, deployment, MLOps, generative AI, responsible AI) but on different platform tooling. Pick based on the platform your target employers use. AWS ML Engineer Associate runs $150, Azure AI Engineer $165, Google Cloud Professional ML Engineer $200.
Exam fees, formats, and recertification windows shown across the DecipherU Applied AI certification catalog reflect publicly listed vendor pricing as of April 2026. Verify current pricing and requirements at the certifying body before registering.