Duration

4 days.

Prerequisites

Before attending this course, students must have:

  • Azure Fundamentals
  • Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
  • How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.

    Who Can Benefit?

    This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

      Outline for Designing and Implementing a Data Science Solution on Azure Training

      Outline

      • Design a data ingestion strategy for machine learning projects
      • Design a machine learning model training solution
      • Design a model deployment solution
      • Explore Azure Machine Learning workspace resources and assets
      • Explore developer tools for workspace interaction
      • Make data available in Azure Machine Learning
      • Work with compute targets in Azure Machine Learning
      • Work with environments in Azure Machine Learning
      • Find the best classification model with Automated Machine Learning
      • Track model training in Jupyter notebooks with MLflow
      • Run a training script as a command job in Azure Machine Learning
      • Track model training with MLflow in jobs
      • Run pipelines in Azure Machine Learning
      • Perform hyperparameter tuning with Azure Machine Learning
      • Deploy a model to a managed online endpoint
      • Deploy a model to a batch endpoint

        01/16/2024 - 01/19/2024
        09:00 AM - 05:00 PM
        Eastern Standard Time
        Online Virtual Class
        USD $2,380.00
        Enroll
        03/11/2024 - 03/14/2024
        09:00 AM - 05:00 PM
        Eastern Standard Time
        Online Virtual Class
        USD $2,380.00
        Enroll
        06/03/2024 - 06/06/2024
        09:00 AM - 05:00 PM
        Eastern Standard Time
        Online Virtual Class
        USD $2,380.00
        Enroll