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Course Outline
Introduction
Overview of MLOps
- Defining MLOps
- MLOps within the Azure Machine Learning architecture
Setting Up the MLOps Environment
- Configuring Azure Machine Learning
Ensuring Model Reproducibility
- Utilizing Azure Machine Learning pipelines
- Integrating machine learning processes with pipelines
Containers and Deployment
- Packaging models into containers
- Deploying containerized models
- Validating model performance
Automating Operational Tasks
- Automating operations using Azure Machine Learning and GitHub
- Retraining and testing models
- Rolling out new model versions
Governance and Control
- Establishing an audit trail
- Managing and monitoring models
Summary and Conclusion
Requirements
- Prior experience with Azure Machine Learning
Target Audience
- Data Scientists
14 Hours
Testimonials (2)
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.
