Designing and Implementing a Data Science Solution on Azure (DP-100) Certification Training

Train, evaluate, deploy, and monitor scalable machine learning models using Azure Machine Learning Studio, MLflow, Automated ML, and Kubernetes endpoints.

Vendor: Microsoft | Duration: 5 Days (40 Hours) | Level: Advanced

Regional Editions: Dubai & UAE Training | South Africa Training

Course Learning Objectives

• Design and prepare machine learning workspaces, compute instances, and datastores on Azure
• Run ML training experiments with the Azure ML Python SDK v2 and MLflow tracking
• Optimize hyperparameters and execute automated machine learning (AutoML) jobs
• Deploy models to real-time managed online endpoints and batch inference pipelines
• Implement responsible AI dashboards, model explainability, and data drift monitoring

Curriculum Modules

• Module 1: Azure Machine Learning Workspace Setup, Compute Clusters & Datasets
• Module 2: Experiment Tracking with MLflow, Model Training & Hyperparameter Tuning
• Module 3: Automated Machine Learning (AutoML) & Azure ML Designer Pipelines
• Module 4: Model Deployment to Managed Online Endpoints & Real-Time Scoring
• Module 5: Responsible AI Framework, Model Drift Monitoring & Certification Prep