Learn how to build, train, and deploy Machine Learning models using Azure Machine Learning in this hands-on DP-3007 webinar designed for data professionals and AI practitioners.
This session provides a practical walkthrough of the full ML lifecycle—from data preparation and model training to deployment and monitoring—leveraging Azure’s powerful tools and services.
Curriculum
- Set up Azure ML environment – Create and configure a workspace and compute resources
- Prepare data – Ingest and process data for training
- Train a model – Use Python and MLflow to train and track models
- Manage artifacts – Log and manage model outputs and metrics
- Deploy the model – Publish to an online endpoint for real-time predictions
Who is this webinar for?
- Data Scientists looking to operationalize ML models using Azure tools
- AI/ML Engineers focused on model training, deployment, and lifecycle management
- Data Analysts interested in expanding into ML workflows
- Developers who integrate ML models into applications and services
- Technical Decision Makers who evaluate Azure ML for enterprise AI solutions