Machine Learning on Azure

As a data scientist, you might be interested in how to improve the development in an ML lifecycle and bring ML algorithms faster to production or overcome challenges with the current development cycle. In this 2-day training in Machine Learning on Azur,e 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, and how to easily deploy and serve models. The training explains all the principles and is supported with practical exercises to cover the end-to-end ML lifecycle.

Training objective

The objective of this 2-day training is to learn how you can manage your end-to-end Machine Learning lifecycle in Microsoft Azure and Databricks.

Audience

• You are a Data Scientist or Data Engineer interested in running ML on Azure
• You are interested in learning how you can build and deploy ML in the Azure cloud
• You want to know some best practices for running ML in Azure
• You want hands-on exercises to learn how to do an end-to-end ML lifecycle management

Agenda

During this 2-day training, 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 training

Day 1

• 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

Day 2

• Deep dive into Databricks as an ML Analytics Platform
• Hands-on Machine Learning use case using MLflow, AutoML & feature stores

The training offers 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                   

More information or registration

• For more information, contact academy@element61.be
• The training schedule can be found in the Academy Calendar (PDF)
• For a complete overview of all training, visit our Academy page