Behind the Scenes with Microsoft Azure

Tejul Pandit is passionate about leveraging the power of artificial intelligence to build data-backed solutions. That passion is what drew her to Northwestern Engineering's Master of Science in Artificial Intelligence (MSAI) program, and it's why she was excited to participate in a recent training session organized by Microsoft to introduce students to Microsoft Azure.

The Azure cloud platform is a collection of more than 200 products and services designed to help businesses solve today’s challenge and build for the future. 

Pandit had never worked with Microsoft Azure before the workshop. 

"The session was a thorough and structured flow of all the services that are available on Azure," she said. "The instructors covered a lot of ground in a very limited time frame."

Current student Aziza Mirsaidova agreed. Mirsaidova is interested in learning and experimenting with how to deploy predictive models and optimize their performance, so when she heard about a chance to go behind the scenes with Microsoft Azure to understand how the system works and can be leveraged, she jumped at the opportunity.

"My primary goal was to increase my understanding of the application systems used for efficient dataflow and learn about machine learning operations and deployment systems," she said. 

The students were introduced to the Azure ecosystem and discussed advanced analytics systems that allowed them to combine data in order to build and deploy custom machine learning models at scale. They learned about choosing data storage services and data movement tools. They also gained experience with Microsoft Portfolio for AI and Azure ML Services to deploy machine learning models. 

Mirsaidova said that understanding different storage systems, computing efficiencies, and machine learning operations will help them bring efficient, innovative, and practical solutions to organizations.

Will Johnson, director of cloud analytics at Microsoft, felt the same way.

“The students of the MSAI program are now ready to jump into organizations ranging from those entering into the cloud all the way to organizations leveraging the cloud to the fullest extent,” Johnson said. “Their broad exposure to cloud storage and computing concepts gives them the context to make and understand tradeoffs between cloud offerings.”

Earlier this year, MSAI hosted a similar training session for Amazon Web Services (AWS). Johnson said these events are examples of the emphasis Northwestern and the MSAI program places on turning out high-caliber students.  

“I am impressed with the program’s focus on ensuring their students are not only successful in industry but also that the MSAI students are ready to lead in their industry,” he said. “Northwestern certainly serves as a model for other universities in preparing their students for working in the applied machine learning and artificial intelligence domains.” 

That’s exactly what Pandit wants to do once she completes the MSAI program. Her drive is to become a machine learning engineer. She came away from the training impressed with how simple it was to deploy a machine learning model with Azure. 

While students were gaining a deeper understanding of Azure, the Microsoft team was learning more about the MSAI students’ talents. Johnson said the students’ technical knowledge, creativity and resourcefulness were impressive. 

“Having only had a few quarters into their program, many students were capable of using state-of-the-art deep learning techniques to solve the set of challenges provided during the workshop,” he said. “As each student could solve the challenge in their own way, they were quick to research, experiment and take paths that were unexpected to us but were viable solutions.”