What You'll Learn

  • Assess readiness for the DP-100 exam through realistic Azure Machine Learning scenarios and detailed answer explanations.,Design and prepare machine learning solutions using Azure Machine Learning workspaces
  • data assets
  • compute
  • and environments.,Train
  • optimize
  • and evaluate models using MLflow
  • AutoML
  • hyperparameter tuning
  • responsible AI
  • and experiment tracking.,Deploy
  • monitor
  • and manage production ML models using endpoints
  • pipelines
  • registries
  • automation
  • and MLOps practices.

Requirements

  • Basic knowledge of Python
  • machine learning
  • Azure
  • data science
  • model training
  • evaluation
  • deployment
  • and MLOps concepts is recommended.

Description

Prepare with six comprehensive DP-100-style practice exams containing 600 scenario-based questions focused on the skills previously measured by the Microsoft Azure Data Scientist Associate certification.

This course is designed for Azure data scientists, machine learning engineers, AI engineers, cloud professionals, developers, and learners who want to review practical Azure Machine Learning concepts through exam-style scenarios.

The practice exams cover designing and preparing machine learning solutions, including Azure Machine Learning workspaces, data assets, datastores, compute resources, environments, registries, identities, permissions, and source control integration.

You will also practice data exploration and experimentation topics such as notebooks, Spark-based processing, feature stores, AutoML, MLflow experiment tracking, model evaluation, responsible AI, hyperparameter tuning, primary metrics, and early termination strategies.

Model training and deployment scenarios include Azure Machine Learning jobs, reusable pipeline components, scheduled pipelines, model registration, MLflow model signatures, online endpoints, batch endpoints, deployment testing, controlled rollouts, monitoring, drift detection, and production MLOps practices.

The course also reviews language model optimization skills previously included in DP-100. Topics include model selection, prompt engineering, prompt templates, prompt flow, tracing, retrieval-augmented generation, embeddings, vector stores, Azure AI Search, RAG evaluation, and fine-tuning workflows.

Every question includes explanations for the correct answer and each incorrect option. These explanations help you understand the reasoning behind each choice, distinguish between similar Azure capabilities, and identify areas that require additional study.

By completing all six practice exams, you can review legacy DP-100 objectives, strengthen Azure Machine Learning knowledge, improve practical data science decision-making, and build confidence through 600 professional practice questions.

Important: DP-100 was retired by Microsoft on June 1, 2026. This course should therefore be positioned as a legacy skills review and practice resource rather than preparation for an active certification exam.

This course is an independent learning resource and is not affiliated with, sponsored by, or endorsed by Microsoft.

Who this course is for:

  • DP-100 candidates
  • Azure data scientists
  • ML engineers
  • AI engineers
  • cloud professionals
  • and developers working with Azure Machine Learning.
DP-100 Microsoft Azure Data Scientist Associate Test Exams

Course Includes:

  • Price: FREE
  • Enrolled: 0 students
  • Language: English
  • Certificate: Yes
  • Difficulty: Beginner
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