- Learn how to design a data ingestion solution for training data used in machine learning projects.
In this module, you'll learn how to:
- Identify your data source and format
- Choose how to serve data to machine learning workflows
- Design a data ingestion solution
- Design a machine learning model training solution with Azure Machine Learning.
In this module, you learn how to:
- Design a solution to get and prepare data.
- Choose a service and compute to train a model.
- Prepare for model deployment options.
- Design a model deployment solution with Azure Machine Learning Python SDK v2
In this module, you'll learn how to:
- Understand how a model will be consumed.
- Decide whether to deploy your model to a real-time or batch endpoint.
- Design machine learning operations MLOps solution with Azure Machine Learning Python SDK v2.
In this module, you will:
- Explore an MLOps architecture.
- Design for monitoring.
- Design for retraining.
Overview
Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Syllabus
- Design a data ingestion strategy for machine learning projects
- Introduction
- Identify your data source and format
- Choose how to serve data to machine learning workflows
- Design a data ingestion solution
- Exercise: Design a data ingestion strategy
- Module assessment
- Summary
- Get started with machine learning in Azure
- Introduction
- Define the problem
- Get and prepare data
- Train the model
- Use Azure Machine Learning studio
- Integrate a model
- Exercise - Explore Automated Machine Learning in Azure Machine Learning
- Module assessment
- Summary
- Design a model deployment solution
- Introduction
- Understand how model will be consumed
- Decide on real-time or batch deployment
- Module assessment
- Summary
- Design a machine learning operations solution
- Introduction
- Explore an MLOps architecture
- Design for monitoring
- Design for retraining
- Knowledge check
- Summary