Course Overview
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 with Azure Machine Learning and MLflow.
You could also consider this Applied Skill which complements the DP-100 certification by validating real-world experience with Azure ML.
Who should attend
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.
Certifications
This course is part of the following Certifications:
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 containersTo gain these prerequisite skills, take the following free online training before attending the course:
- Explore Microsoft cloud concepts.
- Create machine learning models.
- Administer containers in AzureIf you are completely new to data science and machine learning, please complete Microsoft Azure AI Fundamentals first.
Course Content
- Explore and configure the Azure Machine Learning workspace
- Experiment with Azure Machine Learning
- Optimize model training with Azure Machine Learning
- Manage and review models in Azure Machine Learning
- Deploy and consume models with Azure Machine Learning
- Develop generative AI apps in Azure AI Foundry portal
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