Program Overview & Executive Scope
The DP-100 course prepares data science professionals to build production-grade ML pipelines on Microsoft Azure. Candidates learn to manage Azure ML workspaces, compute targets, and datastores; orchestrate training runs with MLflow; tune hyperparameters; and deploy real-time managed endpoints with Azure Container Instances and AKS.
Key Competencies & What You Will Master
Curriculum & Module Breakdown
Design and Prepare a Machine Learning Solution
Azure ML workspaces, compute targets, datasets, and datastores.
Explore Data and Train Models
Experiment tracking with MLflow, script runs, and Automated ML.
Prepare a Model for Deployment
Model evaluation, Responsible AI components, and pipeline scheduling.
Deploy and Retrain a Model
Online endpoints, batch endpoints, and monitoring in production.
Prerequisites
- •Knowledge of Python, data science principles, and machine learning frameworks (scikit-learn)
Target Audience
- •Data Scientists
- •AI Developers
- •Data Analysts transitioning to ML
Frequently Asked Questions
Yes, all labs and demonstrations use Microsoft's latest Azure Machine Learning Python SDK v2 and CLI v2.
Official Microsoft DP-100 exam voucher included.
Related Certifications in Applied AI, Data & Analytics
AWS Certified Machine Learning – Specialty
Exam Code: MLS-C01 • 100% Sandbox Labs
Google Cloud Professional Data Engineer
Exam Code: GCP-PDE • 100% Sandbox Labs
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