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Designing and Implementing a Data Science Solution on Azure

  • Tuition USD $1,886 Save $210
  • Reviews star_rate star_rate star_rate star_rate star_half 944 Ratings
  • Course Code DP-100T01
  • Duration 3 days
  • Available Formats Virtual, Classroom

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.

Who Can Benefit

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

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.

Course Details

Outline


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

How do I get a Microsoft exam voucher?

Pearson Vue Exam vouchers can be requested and ordered with your course purchase or can be ordered separately by clicking here.

  • Vouchers are non-refundable and non-returnable. Vouchers expire 12 months from the date they are issued unless otherwise specified in the terms and conditions.
  • Voucher expiration dates cannot be extended. The exam must be taken by the expiration date printed on the voucher.

Well-executed course. I had to wait for the last minute to register for the course because of my org – their staff contacted me to ensure that I had a webcam and headset because they wouldn't be able to send me that in time for the start of class the next morning. They overnighted the webcam and headset and it arrived in the afternoon. It was not necessary but very much appreciated! The course was great and the instructor was a pro!

The course is perfectly designed with material and labs to get hands on experience on AWS, nicely done!

Outstanding job on the facilitator of this course (Ruben) and great information taught throughout the duration!

Ruben did a fantastic job facilitating this course! The only downfall is trying to cram all this information into 2 days! Incredibly overwhelming...

Very organized. I like how they keep me informed and prepared for training. I would certainly go to ExitCertified (Tech Data) as a training delivery platform/company again.

Very knowledgeable instructor and good presentation of the concepts. The hands on labs in addition to demos from the instructor supplemented the lecture material well and kept the course engaging.

6 options available

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  • Sep 28, 2020 Sep 30, 2020 (3 days)
    Location
    Virtual
    Language
    English
    Time
    12:00 20:00 EST
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  • Oct 5, 2020 Oct 7, 2020 (3 days)
    Location
    Virtual
    Language
    English
    Time
    09:00 17:00 EST
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    Enroll
  • Nov 9, 2020 Nov 11, 2020 (3 days)
    Location
    iMVP
    Language
    English
    Time
    9:00AM 5:00PM EST
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  • Dec 21, 2020 Dec 23, 2020 (3 days)
    Location
    iMVP
    Language
    English
    Time
    9:00AM 5:00PM EST
    Enroll
    Enroll
  • Jan 4, 2021 Jan 6, 2021 (3 days)
    Location
    Virtual
    Language
    English
    Time
    12:00 20:00 EST
    Enroll
    Enroll
  • Jan 25, 2021 Jan 27, 2021 (3 days)
    Location
    Virtual
    Language
    English
    Time
    09:00 17:00 EST
    Enroll
    Enroll
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