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Designing and implementing a data science solution on azure

 

Designing and implementing a data science solution on azure

Key Features

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Course Description

About the Course

Data Scientist is the central role in developing machine learning models. This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best.

Course Curriculum

Designing and implementing a data science solution on azure

Target Audience

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

Prerequisites

  • 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.
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