As a data scientist you might be interested in how to improve the development in a ML lifecycle and bring ML algorithms faster to production or overcome challenges with the current development cycle. In this 2-day course in Machine Learning on Azure we explain how you can develop and train your machine learning algorithms in Azure and Databricks at scale, MLOps principals to register and track ML models, how to easily deploy and serve models. The course explains all the principles and is supported with practical exercises to cover the end-to-end ML lifecycle.
The objective of this 2-day workshop is to learn how you can manage your end-to-end Machine Learning lifecycle in Microsoft Azure and Databricks.
- You are a Data Scientist or Data Engineer interested in running ML on Azure
- You are interested in learning how you can build deploy ML in the Azure cloud
- You want to know some best practices in running ML in Azure
- You want hands-on exercises to learn how to do an end-to-end ML lifecycle management
During this 2-day course we’ll extensively cover Azure Databricks, Azure Machine Learning and Azure DevOps for building and managing ML on Azure. The following topics will be covered in the course
- Recap - What is Machine Learning?
- What are the advantages of performing ML in the cloud?
- How can we start working in the cloud? What tools are available?
- Walkthrough of Azure ML
- Hands-on Machine Learning use case using pipelines & AutoML
- Deepdive into Databricks as an ML Analytics Platform
- Hands-on Machine Learning use case using MLflow, AutoML & feature stores
The course offers a technical training on these technologies as well. The hands-on sessions will help you to:
- Create ML models in Azure Databricks (Python)
- Create ML models in Azure Machine Learning (Python)
- Register and track models with MLflow and Azure ML
- Deploy models to Azure as APIs
- Build CI/CD for ML model deployment
- Deploy new model version through DevOps
- 1.350 € per participant
For more information, contact email@example.com
Azure Training schedule can be found here.
For a complete overview of all courses, visit our academy page.