Course Overview

Enable data scientists and ML engineers to develop, train, and deploy models using Azure Machine Learning platform.

Course Methodology

1. Overview of Azure ML Studio and its components
2. Data preparation and experiment setup
3. Train and evaluate models using AutoML and notebooks
4. Deploy models to endpoints and monitor performance
5. Run hands-on lab with real-world datasets

Audience

Data scientists, ML engineers, and IT teams building enterprise-grade machine learning solutions.

Competencies

1. Model training and deployment
2. Pipeline orchestration
3. AutoML usage
4. Monitoring and retraining models

Tool Features

1. AutoML and custom training
2. ML pipelines and endpoints
3. Integrated compute resources
4. Real-time model monitoring