azure_bkgd1_1April 7th, 9-5; April 8, 9-12
Duke University Libraries has partnered with Microsoft to host a
workshop about Cloud Computing and how use this technology to help solve the technical side of your research projects.

We invite you to spend some time in this Immersion Experience and see how Microsoft Research use Cloud Computing every day to solve difficult research problems.

To Register, please go to

On April 7-8, Duke researchers can spend time learning how to use
Microsoft’s Cloud Computing environment, Microsoft Azure, to experience how this technology can help you with your research projects.

Azure For Research is an intensive class built by cloud experts at
Microsoft Research. The class is designed to familiarize researchers
and data scientists with the services Azure offers to aid them in their
research, especially with regard to high-performance computing, big-data analysis, and analyzing data streaming from Internet-of-Things (IoT) devices. Instruction is hands-on, with students spending most of the day working proctored labs.

Each student receives an Azure Pass with a $500 Azure credit that can be used well after class is over.

This will be hands-on experience, and we invite you to bring your laptop
(Windows, Linux or Mac) with a modern browser (Chrome, Firefox, Internet Explorer or Microsoft Edge).

Faculty, grad students, or anyone interested in big data and cloud-based

Bring a laptop that run Linux, OS X, or Windows with your favorite
browser installed.

An open mind and a desire to learn; no experience with Azure or cloud
computing required.


Module 1: Introduction to Microsoft Azure

This introductory session provides a broad overview of Azure and the
services it offers. It also discusses cloud computing in general and
ways in which the cloud can be an asset to researchers. At the
conclusion, students activate their Azure Passes and explore the Azure
Portal, which is the primary tool used to manage Azure resources.

Module 2: Azure Machine Learning

Azure Machine Learning is a powerful tool for performing predictive
analytics on large volumes of semi-structured data. In this module,
students use the interactive Azure Machine Learning Studio to build,
train, and score a model. Then they put the model to work performing
predictive analytics.

Module 3: Azure Storage

Azure Storage is a set of services for storing data in the cloud. Of
particular interest to researchers is Azure Blob Storage, which serves
as a source of input and output for Azure data services. In this
session, students learn how to move data in and out of blob storage as a
precursor to working with Stream Analytics and other services that use it.

Module 4: Azure Stream Analytics and the Internet of Things

Azure Stream Analytics is a service that enables researchers to query
and analyze high-velocity data streaming from IoT devices and other
sources in real time. In this module, students combine Azure Stream
Analytics with Azure Event Hubs to perform real-time analytics on data
emanating from simulated ATM machines.

Module 5: Big-Data Analytics with Apache Spark for Azure HDInsight

Some of the most commonly used tools for analyzing big data include
Hadoop, Spark, and Zeppelin. In this session, students learn about Azure
HDInsight (Azure’s implementation of Hadoop), deploy a Linux Spark
cluster, and gain first-hand experience using Zeppelin and Jupyter to
analyze data on the cluster.

Module 6: High-Performance Computing

Big problems require big solutions. One of the benefits of cloud
computing is that with a few button clicks, you can bring the power of
massive parallel processing to bear on projects that require it. In this
module, students deploy a SLURM cluster of Linux servers and use it to
perform parallel processing on image data.

Agenda – Friday, April 8th – 9:00 am – 12:00 pm

We will have a few deep-dive breakout sessions on Friday. The exact
topics are still being determined at this time.

To Register, please go to

The event will be held in The Edge Workshop Room in Bostock Library.

For more information, or for questions, please contact John Bormann at