This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best.

Suggested Prerequisites

AZ-900T00 Microsoft Azure Fundamentals - with Lab

1 - DOING DATA SCIENCE ON AZURE

• Introduce the Data Science Process
• Overview of Azure Data Science Options
• Introduce Azure Notebooks

2 - DOING DATA SCIENCE WITH AZURE MACHINE LEARNING SERVICE

• Introduce Azure Machine Learning (AML) service
• Register and deploy ML models with AML service

3 - AUTOMATE MACHINE LEARNING WITH AZURE MACHINE LEARNING SERVICE

• Automate Machine Learning Model Selection
• Automate Hyperparameter Tuning with HyperDrive

4 - MANAGE AND MONITOR MACHINE LEARNING MODELS WITH THE AZURE MACHINE LEARNING SERVICE

• Manage and Monitor Machine Learning Model