Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.
Prerequisites
Successful Azure Data Scientists start this role with a fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.
Specifically:
Creating cloud resources in Microsoft Azure.
Using Python to explore and visualize data.
Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
Working with containers
Intended Audience
This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
Topics
Introduction to Azure Machine Learning
No-Code Machine Learning with Designer
Running Experiments and Training Models
Working with Data
Compute Contexts
Orchestrating Operations with Pipelines
Deploying and Consuming Models
Training Optimal Models
Interpreting Models
Monitoring Models
Other Trainings
Azure
61 Training Set
