Sergey Baidachnyi
Principal developer evangelist at Microsoft Canada

Topic (Mobile & IoT stream):
"Developing IoT solution from scratch"

Topic (AI & Data Science):
"Azure Machine Learning for Data Scientists"

Sergii Baidachnyi is a principal developer evangelist at Microsoft Canada!

Currently residing in Canada, Sergii is participating in many pilot projects with partners around IoT, Machine Learning and Big Data.
Sergii was introduced to the Microsoft platform for developers circa 2001, and since that time, he has actively participated in a number of .NET projects, developing, managing, and architecting financial, medical, and multimedia applications.
At the same time, Sergii led Microsoft IT Academy, where he delivered .NET-related trainings on C#, Windows Forms, ASP.NET, and so on. He has published articles and reviews in multiple IT-industry magazines and several books on ASP.NET, Silverlight, Windows Forms, and Windows 8 Development. His book about Windows 10 development is available on Amazon
You can read more of Sergii's musings on his blog at http://en.baydachnyy.com.
You can also catch him attending and speaking at Microsoft events around Canada. Sergii's twitter is @sbaidachni.
Thesis to the speech
"Developing IoT solution from scratch"
More demos and less slides: you'll get a chance to join a practical demonstration and see how to develop an IoT solution from scratch using Azure services such as IoT Hub, Azure Stream Analytics and Power BI. We will use a prototyping board as a device. Using a field gateway we will connect the device to the cloud in order to collect, analyze and visualize data from different sensors. To wrap up, we'll discuss several projects in production recently implemented using all services from the demo.

Thesis to the speech
"Azure Machine Learning for Data Scientists"
In this presentation we will discuss some new tools and services that are available for Data Scientist. We will start with Azure ML Workbench and show how to use the tool in order to work with your project in a team. After that we will discuss some deployment options using virtual machines and containers. You will be able to see how to use Batch AI and Azure DataBricks services to create and use clusters of VMs to use modern deep learning frameworks for distributed training of your models.