DP100 Azure Data Scientist Associate Practice Test

About this course

This question bank is designed to help candidates prepare for the latest DP-100 exam scope as defined by Microsoft.Each question reflects the modernized direction of Azure Machine Learning, focusing on:SDK v2 workflows using the Azure AI ML package and MLClient interfaceMLflow integration for experiment tracking, model registry, and deployment lineageAzure AI Services including Prompt Flow, AI Search, RAI dashboards, and OpenAI API on AzureBest practices for MLOps and monitoring using Azure Monitor and Application InsightsResponsible AI, Interpretability, and Model fairnessMigration away from deprecated Designer and SDK v1 patternsThe question set is continuously updated, with new and refined questions added weekly to align with evolving Microsoft documentation and real-world Azure ML practices.Built by practitioners experienced in both data science and Azure ML engineering, this collection emphasizes realistic, scenario-based learning—ensuring you gain not only exam readiness but also practical mastery of the latest Azure AI ecosystem.DP-100: Latest Exam Scope — Key Domains & Topics (Current Latest Version 4/11/2025)High-Level Skill Areas & WeightingsDesign and prepare a machine learning solution — approximately 20-25%Explore data and run experiments — approximately 35-40%Train and deploy models — approximately 20-25%Optimize language models for AI applications — approximately 10-15%Core Topics & Subdomains to CoverDesign & Prepare ML SolutionsSetup and manage Azure ML workspaces, compute targets, and storageChoose appropriate tools, pipelines, and environments for ML workloadsData ingestion, transformation, and feature engineering foundations<

Course objectives

• prepare effectively for the DP-100 certification exam
• gain hands-on experience with Azure's machine learning tools
• stay updated with evolving Microsoft guidelines
• build a practical understanding of MLOps