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.
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.
- Set up an Azure Machine Learning workspace
- Run experiments and train models
- Optimize and manage models
- Deploy and consume models
- Azure Fundamentals
- Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
- How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn
- Module 1: Doing Data Science on Azure
- Introduce the Data Science Process
- Overview of Azure Data Science Options
- Introduce Azure Notebooks
- Module 2: Doing Data Science with Azure Machine Learning service
- Introduce Azure Machine Learning (AML) service
- Register and deploy ML models with AML service
- Module 3: Automate Machine Learning with Azure Machine Learning service
- Automate Machine Learning Model Selection
- Automate Hyperparameter Tuning with HyperDrive
- Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning service
- Manage and Monitor Machine Learning Models
Azure Solutions Architect Expert