Introduction to machine learning operations (MLOps)
Offered By: Microsoft via Microsoft Learn
Course Description
Overview
- Module 1: Learn about DevOps for machine learning, machine learning operations, and MLOps.
In this module, you'll learn:
- Why DevOps is useful for machine learning projects.
- Which DevOps principles can be applied to machine learning projects.
- How to connect Azure DevOps and GitHub with Azure Machine Learning.
- Module 2: Learn about source control for machine learning, machine learning operations, and MLOps.
- Trunk-based development with Git.
- How to work with Git in Azure Repos and GitHub.
- How to develop locally with Visual Studio Code.
- Module 3: Learn about automation for machine learning, machine learning operations, and MLOps.
- How to use Azure Machine Learning pipelines.
- How to use Azure Pipelines and GitHub Actions to automate workflows.
- Module 4: Learn about continuous development for machine learning, machine learning operations, and MLOps.
- How to set up environments for development and production.
- How to control deployments with approval gates.
Syllabus
- Module 1: Module 1: Introduction to DevOps principles for machine learning
- Introduction
- DevOps for machine learning
- DevOps tools
- Integrate Azure Machine Learning with DevOps tools
- Knowledge check
- Summary
- Module 2: Module 2: Source control for machine learning projects
- Introduction
- Repositories and trunk-based development
- Work with Azure Repos and GitHub repos
- Develop locally with Visual Studio Code
- Verify your code locally
- Knowledge check
- Summary
- Module 3: Module 3: Automate machine learning workflows
- Introduction
- Azure Machine Learning pipelines
- Azure Pipelines
- GitHub Actions
- Knowledge check
- Summary
- Module 4: Module 4: Continuous deployment for machine learning
- Introduction
- Set up environments for development and production
- Control deployments with approval gates
- Knowledge check
- Summary
Tags
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