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Microsoft Future Ready: Designing and Implementing a Data Science Solution on Azure

Develop your understanding of how to design and implement a data science solution on Microsoft Azure.

Microsoft Future Ready: Designing and Implementing a Data Science Solution on Azure
  • Duration3 weeks
  • Weekly study6 hours
  • 100% onlineTry this course for free
  • Included in an ExpertTrackCourse 6 of 6
  • Get full ExpertTrack access$39/month

This self-paced course was created by the Microsoft World Wide Learning team for data scientists, with the aim of supporting the exam DP-100: Designing and Implementing a Data Science Solution on Azure.

You’ll learn about the data science process and how solutions within Microsoft Azure can best support it. You’ll then delve into machine learning model training and deployment, allowing you to use a greater degree of automation within your data science projects.

Use the Azure machine learning to improve your data modelling

Machine learning is revolutionising a huge range of industries, including data science. Guided by industry experts, you’ll review the machine learning capabilities available in Microsoft Azure, and learn how to use it for local model training, model selection automation, model management, and monitoring.

Consolidate your knowledge by building a chatbot

Once you have built your understanding of Microsoft Azure and its functionality, you’ll put that knowledge into practice by building a simple chatbot. This offers you the opportunity to customise and troubleshoot within the platform, as well as a chance to build hands-on experience.

By the end of the course you’ll have the confidence and knowledge to design and implement a data science solution using Microsoft Azure’s AI stack.

Syllabus

  • Week 1

    Course Introduction

    • About this Course

      This activity introduces you to the course outline and the learning outcomes. It also explains how to navigate the course on the FutureLearn platform and access the CloudSwyft Hands-On Labs.

    • Data Science

      In this activity, you will learn about data science and the different roles that comprise the data science team.

    • The Data Science Process

      In this activity, you will explore each of the predefined steps involved in the data science process.

    • Azure and Data Science

      In the activity, we will provide a broad overview of Azure services and products used for data science and machine learning.

    • Cloud-based and On-premises Machine Learning

      In this activity, you will examine the functionality and key features of Azure's cloud-based and on-premises machine learning products.

    • Wrapping up the Week

      This is the closing activity for Week 1, where you will have the opportunity to reflect on what you have learned during the week.

  • Week 2

    Data Science on Azure

    • Development platforms and tools

      In this activity, we will review the development platforms and tools that Microsoft provides for machine learning.

    • Introduction to Data Science with Azure Notebooks

      In this activity, you will learn the functionality of Azure Notebooks through a number of exercises.

    • CloudSwyft Hands-On Lab 1

      In this activity, you will put the concepts from the previous activities into action by completing your first CloudSwyft Hands-On Lab.

    • Introducing the Azure Machine Learning (AML) Service

      This activity explains how the Azure Machine Learning service augments and automates the data science process through the use of containerisation and special machine learning services.

    • Training Machine Learning Models

      This activity demonstrates how to use Azure Machine Learning service to select a model, tune hyperparameters, train a model, deploy a model and monitor the deployed model.

    • Wrapping Up the Week

      This is the closing activity for Week 2, where you'll have the opportunity to reflect on what you've learned during the week.

  • Week 3

    Azure Machine Learning Service

    • Registering and Deploying Models

      In this activity, you will create a deployment workspace, learn about registering a model to the container registry, and deploy a model as a web service.

    • CloudSwyft Hands-On Lab 2

      In this activity, you will complete your CloudSwyft Hands-On Lab to put the concepts from the previous activities into action.

    • Automating Model Selection with AML Service

      In this activity, you will learn about the machine learning pipeline and how AML service's AutoML can automate parts of it. You'll also learn about the Machine Learning Operations (MLOps) capabilities that AM Learning provides.

    • CloudSwyft Hands-On Lab 3

      In this activity, you will complete your CloudSwyft Hands-On Lab to put the concepts from the previous activities into action.

    • Managing and Monitoring Models with AML Service

      In this activity, you will learn about Azure Machine Learning service model management, and tracking features that can be integrated into pipelines.

    • Wrapping Up the Course

      This is the closing activity for Week 3 and the course where you'll have the opportunity to reflect on what you have learned!

What will you achieve?

By the end of the course, you‘ll be able to...

  • High level overview of Azure data science related services
  • Deep dive on the premier data science service, Azure Machine Learning service, which supports automation of machine learning model training and deployment.
  • Navigate the Azure portal and to create services there.
  • Familiarity with the Azure data storage technologies

Who is the course for?

This course is best suited to aspiring data scientists and those whose job responsibilities primarily fall into the area of data science.

Who developed the course?

CloudSwyft Global Systems, Inc.

CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.

About this ExpertTrack

Investigate Data Science Fundamentals using Microsoft Azure

Start learning today - free 7-day trial

After your free trial you can:

  • Pay $39 per month to keep learning online
  • Have complete control over your subscription; you can cancel any time
  • Work at your own pace and set your own deadlines at every stage
  • Only pay while you’re learning; the subscription will cancel automatically when you finish
  • Complete online assessments to test your knowledge and prove your skills
  • Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
  • Keep access to the content of courses you complete even after your subscription ends