Azure DP-100 (Data Scientist Associate) was retired June 1, 2026 and replaced by two new tracks: AI-300 MLOps Engineer Associate for Azure-native ML workflows, and DP-750 for Databricks-focused ML engineering. If you were preparing for DP-100, your study materials are now targeting a retired exam. This 30-question check diagnoses how well your preparation maps to the AI-300 and DP-750 objectives, so you can redirect your remaining study time without starting from zero.
Microsoft retired the Azure Data Scientist Associate (DP-100) on June 1, 2026. The replacement tracks split the former DP-100 scope: AI-300 MLOps Engineer Associate covers Azure Machine Learning service, MLOps pipelines, model deployment, and responsible AI; DP-750 (Implementing Data Science Solutions with Microsoft Fabric and Azure Databricks) covers the Databricks and Fabric engineering path. Candidates who prepared for DP-100 typically have 60–70% coverage of the new objectives, but the gap sits in areas like Azure ML pipeline orchestration (AI-300) and Databricks Unity Catalog (DP-750). This free readiness check surfaces exactly where your DP-100 preparation does and does not carry over, so you can make a targeted decision: pursue AI-300, DP-750, or both.
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Yes — Microsoft retired the Azure Data Scientist Associate (DP-100) certification on June 1, 2026. It is no longer available to sit. The closest successor certifications are AI-300 MLOps Engineer Associate (Azure-native path) and DP-750 Implementing Data Science Solutions with Microsoft Fabric and Azure Databricks (Databricks-focused path).
AI-300 is the right choice if you work primarily in Azure Machine Learning service and want to specialise in MLOps, model monitoring, and Azure-native deployment. DP-750 is the better fit if your work is Databricks- or Fabric-heavy and you deal with Delta Live Tables, Unity Catalog, and lakehouse architectures. Many ML engineers on Azure will find AI-300 the cleaner successor to what DP-100 tested.
Roughly 60–70% carries over. Core ML concepts — feature engineering, model evaluation, hyperparameter tuning, cross-validation — are shared across both new exams. What does not carry over: the AI-300 adds deep MLOps pipeline orchestration and responsible AI tooling; DP-750 adds Databricks Unity Catalog, Delta Live Tables, and Fabric-specific patterns that DP-100 did not test.
The full test (Hard mode) has 30 questions across 7 topic areas covering both the AI-300 and DP-750 objective sets, so you can see where your preparation is strongest for each path.
A score of 85–100 places you in the Exam Ready band. 70–84 is Almost Ready — targeted review of your weak areas should close the gap in 1–2 weeks. Below 70, the AI Report ($19) builds a personalised study plan identifying which AI-300 or DP-750 objectives to prioritise.
Completely free — no account or credit card required. After the test you can optionally purchase the AI Report ($19) for a personalised study plan mapped to AI-300 or DP-750 objectives.
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