Azure Internet of Things Edge Development Resources
Published Mar 21 2019 10:02 AM 330 Views
First published on MSDN on Jan 17, 2018

Everyone’s talking about The Internet of Things (IoT)

Some businesses and consumers have already begun embracing it wholeheartedly. Others want to understand it better than they do. And many find the whole idea a bit overwhelming and aren’t sure where to start. Here a typically overview of IOT solution and technologies which could be used to implement a suitable solution.

The Microsoft IOT Team are trying to  bring some clarity with a new article, “ IoT: It’s Easier Than You Might Think ,” where Microsoft IOT team to cut through the hype around IoT. Read the full article for more on how to get started with IoT.

  • Explains how IoT can equip organisations to make better business decisions.
  • Lays out a series of proven steps to help you easily get started with IoT.
  • Shares best practices to keep your IoT journey on the right path for long-term success.

Bringing IoT into your curriculum and projects doesn’t have to be difficult, and it certainly doesn’t have to happen all at once!

We recently worked with the University of Oxford on the following course

Overview Data Science for the Internet of Things (IoT)This unique course aims to create a new breed of engineer - those with a background in IoT and knowledge of machine learning, AI, cloud and robotics.

The Data Science for IoT course aims to equip you with the skills to solve problems, providing you with a toolkit (code) and templates. It's for developers who want to be data scientists with an emphasis on IoT.

The course explores problem solving for IoT analytics via the following topics:

  • Concepts: principles/foundations
  • Product development for IoT (with an emphasis on analytics)
  • Data science
  • Artificial intelligence (AI)
  • TensorFlow and Keras
  • Deploying AI models to scale (e.g. via Kubernetes)
  • IoT Verticals
  • Programming
  • Statistics
  • Time series
  • Deep learning
  • Real time including LSTMs and streaming
  • NoSQL databases for IoT
  • IoT data visualization
  • Industrial IoT
  • Robotics and drones
  • Edge analytics
  • Complex event processing
  • Innovation in IoT
  • Methodology – putting it all together
About the course and its aims:
  • The course analyses problem solving for IoT analytics.
  • The unique considerations for IoT data (e.g. time series data) are investigated.
  • The course covers programming so participants will need to be familiar with some programming languages - but we do not expect familiarity in a specific language. The primary programming language of the course is Python (specifically TensorFlow and Keras).
  • We use Spark for big data.
  • The course needs an understanding of maths. We cover maths and statistics foundations  as needed.
  • Where possible, we use IoT datasets. We cover handling large-scale IoT datasets.
  • We focus on skills based/commercial products. This is not an academic course.
  • The course also includes an industry programme. The industry programme will be based on use cases incorporating IoT analytics methodology.

Looking for IOT resources my colleague Jon Gallant has created this collection of resources for Azure IoT Edge development.  which is maintained at

Resources Blogs Dev Tools Videos Modules
  • UDP - Build Azure IoT Edge solutions with UDP connectivity. Creates an UDP endpoint and routes messages to the EdgeHub.
  • OPC-UA Client - Template for creating OPC-UA client modules.
  • Monitoring Module - If you integrate this module in your EdgeHub deployment you can basically monitor all traffic between modules
Other Support

To learn more about how IoT, visit .

Version history
Last update:
‎Mar 21 2019 10:02 AM
Updated by: