Machine Learning on Azure

Service offerings

Technologies

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 1-day course in Machine Learning on Azure we explain how you can develop and train your machine learning algorithms in Azure 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.

Course objective

The objective of this 1-day workshop is to learn how you can manage your end-to-end Machine Learning lifecycle in Microsoft Azure.  

Audience

  • 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

Agenda

During this one-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

  • ML development
    • Using Databricks
    • Using Azure Machine Learning
  • MLOps principles
    • What & Why
    • How to manage the machine learning lifecycle
    • Register and track models
    • Deploy production ready ML models anywhere
  • MLOps in Azure
    • Using Databricks and MLflow
    • Using Azure Machine Learning
  • DevOps for Deployment
    • Azure Pipelines for deployment
    • Packaging Python libraries
  • Serve ML models
    • Using Azure Kubernetes Service
    • API frameworks

 

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

 

Machine Learning on Azure            Machine Learning on Azure            Machine Learning on Azure

Cost

  • 625 € per participant

Subscribe

For more information, contact academy@element61.be

Azure Training schedule can be found here.

For a complete overview of all courses, visit our academy page.