DP-100 - Microsoft Certified: Azure Data Scientist Associate

Microsoft cours officiels

Ces cours sont dispensés en français sur la base d'une documentation pédagogique en anglais.
This course is designed for IT Professionals who will learn how determine what data is needed for model training, create model features from the data, determine what machine learning model to use, train and evaluate the model.
This course help prepare for the exam « DP-100 - Designing and Implementing a Data Science Solution on Azure » to obtain the title « Microsoft Certified: Azure Data Scientist Associate ».

Modules et dates

DP-100 - Microsoft Certified: Azure Data Scientist Associate
Cycle 1
Durée
3
Prix
2'250.-
Prix/J
750.-
on demand
The course is given in French on the basis of documentation in French if available (Fra) or in English (Eng). If it is available in both languages, the French version is distributed unless specifically requested by the interested party. The price of the course includes all the pedagogical documentation distributed.

DP-100 - Microsoft Azure Certified: Data Scientist Associate

Ces cours sont dispensés en français sur la base d'une documentation pédagogique en anglais.
This course is designed for IT Professionals who will learn how determine what data is needed for model training, create model features from the data, determine what machine learning model to use, train and evaluate the model.
This course help prepare for the exam « DP-100 - Designing and Implementing a Data Science Solution on Azure » to obtain the title « Microsoft Certified: Azure Data Scientist Associate ».
  • data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.

Overview

In this 3-day course, IT Professionals learn:
  • how to operate machine learning solutions at cloud scale using Azure Machine Learning
  • leverage your existing knowledge of Python and machine learning
  • manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

Target Audience :

  • data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.

Objectives :

After completing this course, students will be able to:
  • explain the data science process and the role of the data scientist.
  • use Azure Machine Learning service to automate the data science process end to end.
  • explain the machine learning pipeline and how the Azure Machine Learning service's AutoML and HyperDrive can automate some of the laborious parts of it.
  • automatically manage and monitor machine learning models in the Azure Machine Learning service.

Prerequisites :

Before attending this course, students must have:
  • fundamental knowledge of Microsoft Azure
  • understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
  • experience of writing Python code to work with data, using libraries such as Numpy, Pandas, and Matplotlib.

Program :

This course is composed of 4 modules including lessons and practical work (lab).
Module 1: Doing Data Science on Azure

The student will learn about the data science process and the role of the data scientist. This is then applied to understand how Azure services can support and augment the data science process.

Lessons
  • Introduce the Data Science Process
  • Overview of Azure Data Science Options
  • Introduce Azure Notebooks


Module 2: Doing Data Science with Azure Machine Learning service

The student will learn how to use Azure Machine Learning service to automate the data science process end to end.

Lessons
  • Introduce Azure Machine Learning (AML) service
  • Register and deploy ML models with AML service


Module 3: Automate Machine Learning with Azure Machine Learning service

In this Module, the student will learn about the machine learning pipeline and how the Azure Machine Learning service’s AutoML and HyperDrive can automate some of the laborious parts of it.

Lessons
  • Automate Machine Learning Model Selection
  • Automate Hyperparameter Tuning with HyperDrive
Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning service

In this Module, the student will learn how to automatically manage and monitor machine learning models in the Azure Machine Learning service.

Lessons
  • Manage and Monitor Machine Learning Models
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