Exams covering generative AI, model deployment, MLOps and responsible AI practice.
AI certification is the fastest-moving category in this catalog. Foundational exams appeared across every major vendor within a two-year window, and they focus less on mathematics than on service selection, prompt design, evaluation and governance.
Engineer-level exams go deeper: feature pipelines, training and tuning, deployment topologies, drift monitoring and the operational cost of inference.
A foundational AI credential covering machine learning basics, generative AI concepts, prompt engineering, foundation model selection and responsible AI governance on AWS.
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15 exams
14 with practice · 1 guide only
A foundational AI credential covering machine learning basics, generative AI concepts, prompt engineering, foundation model selection and responsible AI governance on AWS.
An accessible introduction to AI on Azure: machine learning principles, computer vision, language processing and generative AI, plus responsible AI considerations.
Building AI applications on Azure: provisioning and securing AI services, generative AI and agent solutions, computer vision, language understanding and knowledge mining.
The MLOps-oriented associate exam: preparing data for training, developing and tuning models, deploying inference workloads, and monitoring them once they are live.
Designing and operating data systems on Google Cloud: processing system design, ingestion and transformation, storage selection, analysis enablement and workload automation.
Production machine learning on Google Cloud: framing problems, building and scaling models on Vertex AI, serving them reliably, and automating and monitoring the pipeline.
The long-running specialty ML exam, weighted heavily toward modelling: algorithm selection, feature engineering, evaluation metrics and production ML operations on AWS.
Configuring generative AI on the Salesforce platform: prompt templates, Einstein generative features, agent configuration, grounding with CRM data, and AI governance.
Machine learning on Databricks at associate level: the ML platform and MLflow, data preparation and feature engineering, model development, and deployment and lifecycle management.
A conceptual AI credential for the Salesforce ecosystem: AI fundamentals, the role of data quality, ethical and responsible use, and Einstein capabilities across CRM.
Planning, designing and deploying AI-powered business solutions across Microsoft business applications — scoping the opportunity, shaping the design, then rolling it out.
A methodology-led AI credential rather than a modelling one: running AI and machine-learning projects through a phased, data-first lifecycle from business understanding to deployment.
A business-value exam rather than a technical one: what generative AI is worth to an organisation, what Microsoft AI apps and services can do, and how to plan adoption.
An advanced audit credential aimed at AI systems: governance and risk frameworks for AI, auditing models and data pipelines, and reporting on AI assurance.
An entry-level AI exam on Oracle Cloud: machine learning and deep learning concepts, generative AI and large language models, and the OCI AI services that implement them.
How many exams each provider contributes here.
Where each exam sits, so you can plan a progression rather than a single jump.
15 exams from 8 vendors are tagged to AI & Machine Learning. Exams appear in this category when it is either their primary focus or a substantial secondary one.
AWS Certified AI Practitioner (AIF-C01) is the most common entry point. A foundational AI credential covering machine learning basics, generative AI concepts, prompt engineering, foundation model selection and responsible AI governance on AWS.
AWS Certified AI Practitioner (AIF-C01), Microsoft Azure AI Fundamentals (AI-900) and Designing and Implementing a Microsoft Azure AI Solution (AI-102) are the most frequently pursued in this category.
Data & Analytics
Data engineering, warehousing, business intelligence and analytics platform certifications.
Cloud Computing
Certifications covering public cloud platforms, architecture, migration and cost management.
DevOps & SRE
Continuous delivery, infrastructure as code, observability and site reliability engineering exams.