DP-100 Microsoft Azure DS Exam
Learn how to design, develop, automate, and deploy end-to-end machine learning solutions using Microsoft Azure Machine Learning. In this course, you will build practical skills in configuring Azure ML workspaces, managing datasets, creating machine learning pipelines with Azure ML Designer, developing code-driven workflows with the Azure ML SDK, and deploying trained models for real-time and batch inference.
Designed for learners who want to build expertise in Azure Machine Learning, this course guides you through the complete machine learning lifecycle—from environment setup and experimentation to automation and production deployment. You will configure compute resources, construct and evaluate pipelines, automate model training with AutoML and HyperDrive, and publish inference pipelines using both the Azure ML Designer and SDK.
What makes this course unique is its balanced approach to visual and code-based development, enabling you to understand how Azure ML Designer and the Azure ML SDK work together to support scalable machine learning workflows. Each module builds progressively through scenario-driven lessons that reinforce practical implementation and evaluation of Azure Machine Learning solutions.
By the end of the course, you will be able to confidently configure Azure ML environments, develop automated machine learning workflows, optimize experiments, and deploy production-ready machine learning models using Microsoft Azure Machine Learning.
Status: Model Evaluation
Model EvaluationStatus: Applied Machine Learning
Applied Machine LearningIntermediate·Course·10 hours
