Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
DP-100: Azure Data Scientist Associate Exam Prep
New

DP-100: Azure Data Scientist Associate Exam Prep

Master Azure ML SDK v2, MLflow, AutoML, and Responsible AI across all four DP-100 exam domains
Created byAseem Mankotia
Last updated 9/2026
English

What you'll learn

  • Create and manage datastores, data assets, and MLTable definitions in Azure ML
  • Track experiments and log metrics with MLflow autologging
  • Submit command jobs and sweep jobs using the SDK v2 for custom training and hyperparameter tuning
  • Configure AutoML jobs for classification, regression, forecasting, and computer vision

Course content

13 sections • 12 lectures

  • Data in Azure ML: Datastores, Data Assets & MLTable12:48

Requirements

  • Working Python programming experience and core ML knowledge (train/validate/test splits, common algorithms, evaluation metrics)

Description

This course contains the use of artificial intelligence.

DP-100 (Microsoft Certified: Azure Data Scientist Associate) validates that you can design, build, and operationalize machine learning solutions on Azure Machine Learning using the current Python SDK v2 (azure-ai-ml) and MLflow. This exam-focused preparation course, built and narrated by Aseem Mankotia, walks through all four official Skills Measured domains in exam order: exploring data and training models, designing and preparing a machine learning solution, preparing a model for deployment, and deploying and retraining a model. Every chapter maps directly to an exam objective, spends the most time on the heaviest-weighted domain (Explore data and train models), and pairs each concept with a hands-on Azure ML Studio or SDK v2 walkthrough covering datastores and MLTable, command jobs and sweep jobs, AutoML for classification, regression, and forecasting, the Responsible AI dashboard, and deployment to managed online and batch endpoints.

Expect zero filler: direct technical explanations, real service limits and configuration values, exam-style scenario questions with full rationale for every option, and a closing full-length 120-minute exam simulation with a time-management strategy for case studies, drag-and-drop, and code-completion items. This course complements the catalog's AI-300 (MLOps) and DP-600 (Fabric Analytics Engineer) paths without overlapping them. DP-100 is specifically about building and operationalizing models on Azure Machine Learning. Exam details such as the current Skills Measured outline, question count, duration, scoring, and fees change over time, so confirm them on the official Microsoft Learn DP-100 page before registering.

AI content disclosure: This course was produced with the assistance of artificial intelligence tools. Lecture narration is AI-voice generated, and lecture scripts, slides, and practice questions were drafted with AI assistance, then reviewed and curated by the instructor for technical accuracy and alignment with the official DP-100 exam guide.

Who this course is for:

  • Data scientists and ML engineers who build and operationalize models on Azure Machine Learning, plus data professionals moving ML workloads to Azure. Assumes working Python and core ML knowledge (train/validate/test, metrics, common algorithms). A cloud-ML step that complements the catalog's AI-300 (MLOps) and DP-600 (Fabric Analytics Engineer) courses.

Report abuse