Unique training package in three sections + three (3) months Ekkono Developer License at 2,500€!
Every product company needs an edge strategy. Edge means automation, and automation means machine learning. This Machine Learning Training Package is a comprehensive tutorial to do a take-off on edge machine learning. After completing this course, you will know all you need know for your first pilot of an implementation.
About the Machine Learning Training Package
The first section gives you a comprehensive introduction to edge machine learning. You will learn about the benefits of running at the edge, and when it is applicable to use this technology.
The second section covers a wide range of use cases. For example condition-based maintenance, smart battery management and virtual sensors. The subject is approached from a technical implementation perspective. We will apply what you learned in the first section to solve real and relevant IoT challenges.
Finally, In the third section we go into the nitty gritty of different edge machine learning techniques. We will talk about online learning, change detection and how to optimize models for microcontrollers. In this section, we will bring it all together in a hands-on exercise. Here you will apply your new learnings from the previous sections into a real machine learning solution using Ekkono Studio and our SDK. During the course you will also get the chance to ask questions to Ekkono’s experts including three PhD’s within the field of machine learning.
This training package is designed for software engineers. The implementation in the third section will be done using Python and Ekkono’s SDK. You might find it valuable to have some Python programming skills to fully enjoy the course, but it is not required.
- Target audience: Technical (the technical implementation section requires programming skills)
- Price: 2,500€/attendee
- Content: Three (3) sections (edge machine learning, use cases, technical implementation) + a three (3) months Ekkono Developer License (one developer seat)