Learning Paths

Implementing the Data Science Workflow in Microsoft Azure

9 courses
14 hours
Skill IQ

Microsoft Azure contains a massive offering of services that can be used together to implement the data science workflow. This path walks you through this workflow, as it is implemented in Microsoft Azure.

Courses in this path

Beginner

In this section of the path, learners will work through data sourcing and preparation. In addition, the features of Microsoft Azure that help with data exploration are highlighted.

Building Your First Data Science Project in Microsoft Azure

by Jared Rhodes
1h 25m
(25)

Sourcing Data in Microsoft Azure

by Jared Rhodes
1h 12m
(11)

Cleaning and Preparing Data in Microsoft Azure

by Jared Rhodes
1h 7m

Exploring Data in Microsoft Azure Using Kusto Query Language and Azure Data Explorer

by Neeraj Kumar
2h 45m
(21)

Intermediate

These courses will inform learners on selecting and extracting features using Microsoft Azure services, then building models that consume those features and evaluating their validity.

Feature Selection and Extraction in Microsoft Azure

by Xavier Morera
1h 27m

Developing Models in Microsoft Azure

by Saravanan Dhandapani
1h 55m
(15)

Evaluating Model Effectiveness in Microsoft Azure

by Tim Warner
50m

Advanced

In this final segment of the path, learners will deploy and manage their models in the Microsoft Azure platform, and learn how to use features of the platform to communicate data insights with others.

Deploying and Managing Models in Microsoft Azure

by Jared Rhodes
59m
(14)

Communicating Insights from Microsoft Azure to the Business

by Neeraj Kumar
2h 24m

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What you will learn

Source, clean, and prepare data using Microsoft Azure
Implement feature selection using Microsoft Azure
Build models and evaluate their effectiveness in Microsoft Azure
Use Microsoft Azure services to deploy and manage your model
Communicate results to the business using the Microsoft Azure platform

Experience

This path is intended for experienced data scientists interested in understanding how their everyday workflows are enabled by Microsoft Azure. It is expected that the learner understand basic data science principles, such as data munging and cleaning, model selection and implementation, and data communication.

Learn with the best

Jared Rhodes

Jared Rhodes has been working in technology for about 10 years. When he started his education, he didn't consider any of the aspects of software development. For his major, he studied physics. Once he graduated, the job market thought his skills were geared towards software development more than physics. His career started at a solar power installer. It was the same as most careers, fixing web pages and batch jobs. After that, he moved into insurance for a year writing a rating engine to give ra... more

Neeraj Kumar

Neeraj is an Azure Enthusiast, Enterprise Architect, and Technical Program Manager. With an IT experience spanning 21 years, Neeraj is leading high-end programs focused on digital and cloud services by architecting and designing solutions and infrastructure on Azure that includes, but not limited to Cognitive Services, Data Science, IoT, Cloud Migrations, etc. to benefit business by maximizing their RoI. Neeraj is a certified Azure Architect, Administrator, and IoT Developer and is passionate ab... more

Xavier Morera

Xavier is very passionate about teaching, helping others understand search and Big Data. He is also an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP. He has spent a great deal of his career working on cutting-edge projects with a primary focus on .NET, Solr, and Hadoop among a few other interesting technologies. Throughout multiple projects, he has acquired skills to deal... more

Saravanan Dhandapani

I have worked in IT design, development, and architecture for over a decade for some of the top fortune 100 companies. I have designed and architected enterprise applications and developed scalable and portable software. I am a Google Certified Professional Architect. Critical areas where I have worked are architecture and design using Java, ESB, Tomcat, ReactJS, JavaScript, Linux, Oracle, SVN, GIT, and so on, and cloud technologies, including AWS and GCP.

Tim Warner

Timothy Warner is a Microsoft Most Valuable Professional (MVP) in Cloud and Datacenter Management who is based in Nashville, TN. His professional specialties include Microsoft Azure, cross-platform PowerShell, and all things Windows Server-related. You can reach Tim via Twitter (@TechTrainerTim), LinkedIn or his blog, AzureDepot.com.

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Learning Paths

Implementing the Data Science Workflow in Microsoft Azure