Course Outline
Introduction
MLOps Overview
- What is MLOps?
- MLOps in Azure Machine Learning architecture
Preparing the MLOps Environment
- Setting up Azure Machine Learning
Model Reproducibility
- Working with Azure Machine Learning pipelines
- Bridging Machine Learning processes with pipelines
Containers and Deployment
- Packaging models into containers
- Deploying containers
- Validating models
Automating Operations
- Automating operations with Azure Machine Learning and GitHub
- Retraining and testing models
- Rolling out new models
Governance and Control
- Creating an audit trail
- Managing and monitoring models
Summary and Conclusion
Requirements
- Prior experience with Azure Machine Learning
Audience
- Data Scientists
Testimonials (3)
It was very much what we asked for—and quite a balanced amount of content and exercises that covered the different profiles of the engineers in the company who participated.
Arturo Sanchez - INAIT SA
Course - Microsoft Azure Infrastructure and Deployment
The course, Trainer
Novat Adam - Tanzania Revenue Authority
Course - Architecting Microsoft Azure Solutions
That we could do everything in practice by ourselves. That our trainer had extensive knowledge and we could ask him anything and he always had the answer. That I got some skills that are useful for developers.
