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Designing and Implementing a Data Science Solution on Azure

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Designing and Implementing a Data Science Solution on Azure

DP-100

Master Azure Machine Learning with hands-on DP-100 training. Build, deploy, and monitor ML solutions at scale. Prepare for Azure Data Scientist Associate certification with expert-led instruction and real-world projects.

Target Audience: Data Scientists
Duration: 4.0000 Days
Job Role: Database Administration
Skill Level: Intermediate

🚀 Transform Your Data Science Career with Azure ML Expertise

This comprehensive 4-day instructor-led DP-100 course equips you with the skills to design, build, and operationalize enterprise-grade machine learning solutions using Azure Machine Learning. Perfect for data scientists and ML engineers, this training combines deep technical instruction with 40-50% hands-on labs to ensure you master every aspect of the Azure ML workflow.

💡 What You'll Master

  • End-to-End ML Workflows: Design workspaces, manage data assets, and configure compute resources using Python SDK v2, Azure CLI, and Studio
  • Advanced Model Training: Leverage MLflow tracking, Automated ML, and hyperparameter tuning to build optimized models
  • Production Deployment: Deploy models to real-time and batch endpoints with scaling, versioning, and authentication
  • MLOps Excellence: Build reproducible ML pipelines, implement CI/CD patterns, and automate retraining workflows
  • Responsible AI: Embed fairness, interpretability, and bias detection into your models with built-in dashboards
  • Monitoring & Governance: Track model drift, performance metrics, and maintain production reliability

🎯 Certification-Ready Training

Aligns perfectly with the Microsoft Certified: Azure Data Scientist Associate (DP-100) exam. Gain practical experience with real-world scenarios that mirror production environments, ensuring you're ready to implement Azure ML solutions from day one.

👥 Ideal For

Data Scientists, ML Engineers, AI Developers, and professionals seeking to operationalize machine learning at cloud scale using Azure's powerful ML platform.

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