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Master Class Sessions ‘Data-driven Innovation Beyond the Hype’

Data-driven innovation aims to support business opportunities enabled by exploiting and leveraging diverse industrial and business data sources. While a lot of attention is currently given to examples by major internet companies (e.g., Google, Amazon, Facebook), data science can also be very valuable to innovate within other research and industrial domains and within SMEs, e.g., to derive insights from experimental data, to profile products and customers, to optimize production processes, to predict the failure of machines, or even to build data-centered startups.

The Master Class Sessions are of interest to everyone who needs to translate business opportunities into solvable technological problems, who wants to explore the new opportunities that are generated by the increasingly available stream of data, or who needs to steer or participate in a team of data scientists. Each of these sessions can be followed independently of one another. All the theoretical data knowledge is illustrated by actual industrial cases from current Data Innovation projects at Sirris.

The course schedule is regularly updated with sessions on additional topics.


Any intelligent algorithm that is used to learn something from data requires that this data is presented in the most optimal way. The process of transforming the data and extracting the most relevant distinguishing characteristics out of it is called feature engineering. It is arguably the most important step in the data science workflow as event the most intelligent algorithm will not produce satisfactory results if the used data does not capture the most essential properties of the phenomenon under study. There is no clearly-defined formak process for engineering features and consequently this requires a lot of creativity, iterations, domain knowledget, etc.

The goal of this session is to give an overview of the most commonly used approaches as well as lessons learnt and common pitfalls for different types of data (sensor data, location data, etc.) and problem settings (prediction, profiling , etc.).

Registration link:

Modules coming up (Autumn 2017):

  • The art of formulating a data science task
  • The necessity of data preparation
  • Choosing the right algorithm for the right task

Each of the sessions can be followed independently of one another.


  • € 525 session
  • Early bird rate (registration more than 4 weeks in advance): € 475/session
  • Training in residence: starting from 4 people of the same company, we can organize this course at your company’s premises. This is offered at a fixed price of € 1950 for half a day training for 4 participants (each additional participant 150 EUR, with a maximum of 10 participants). In this case, please contact Caroline Mair ( Furthermore, we also offer on-request sessions on particular data innovation challenges you are facing. Feel free to contact us for more information.

The course notes are included in the registration price.

If you are a Flemish SME you can also make use of the SME portfolio. For more information, please visit or contact us (

EluciDATA core user group members benefit from a discount on the subscription fee (50% for demonstrator ambassadors/committed technology experts, 25% for engaged advisors, and 10% for the satellite interest group).

Each of the sessions starts at 13:00 and ends at 17:30. The sessions are organized at one of the Sirris sites (indicated per session). Each of the locations is easily reachable, and provides sufficient parking possibility. Route descriptions per site can be found on