Internet of Things (IoT) is without a doubt the next big disruption on the Internet. This is because processors and sensors have become significantly cheaper, making it feasible to put them in virtually everything from running shoes and lawnmowers, to windmills, robots and light posts.

But IoT cannot be handled as an isolated technology question. Connecting your products, making them smart, and gathering valuable user data, comes with several business and organizational decisions. No company can afford to sit passive on the sideline. Unless your company figures out how IoT will disrupt your business, someone else will.

It is crucial that the entire organization, and especially engineering who see the prospects and limitations of the technology, understand and take an active role in defining the IoT strategy. The purpose of this course is to give you tools, inspiration and facts to comfortably and successfully engage in this work.



This course will go through definitions and terminology of IoT. We look at best practice and failures from previous disruptions in internet usage, such as the introduction of smartphones. We look at what is different this time, for example that there is no human operating IoT, which requires connected things to become smart; See course no 101 "Machine Learning For Internet of Things" on how IoT relates to Machine Learning.

No specific equipment is required, though the extensive references to companies and online resources is a good reason to bring a web browsing device.


The course is intended for engineers and project managers who want to advance in a holistic perspective and a business understanding around IoT, to help facilitate projects internally for future IoT enabled product development.

For engineers, the course is favorably combined with course No 101 "Machine Learning For Internet of Things" where we over three days learn how connected things become smart through machine learning.


Day 1

    • Introduction
    • IoT (Internet of Things)
      • Definitions
      • Why now?
      • Who cares?
    • Historical Disruptions
      • Best Practice
      • Failures
      • Learning Experiences
      • What's different now?
    • Business impact
      • Make More Money
        • New Offerings
        • Premium Offerings
      • Save Money
        • Man Power
      • Better Offerings
        • Faster, Better, Cheaper
      • New Business Models
        • Product as a Service and Service as a Product
        • Adaptive Pricing
        • User Data

Day 2

      • Recap of day 1
      • Industrial IoT, IIoT
        • Predictive Maintenance (and Self-Healing)
        • Production Optimization
        • Sales-Driven Sales
      • Consumer IoT
        • Intuitive Products
        • Marketing-Driven Sales
      • Use Cases
      • Hands-on Exercise
        • Business Model Canvas
        • Review
      • Summary and Conclusions