Find out how data innovation works
Are you interested in applying data science and AI to solve a specific business challenge?  But you’re not sure where to start? Enroll in our Mastercourse ‘Data innovation beyond the hype’. As a participant, you will learn more about the different steps of the data analysis process, and gain tailor-made insights on how data science can help you reach your goals. Discover our upcoming webinars and book your seat now.

Future-proof your business. Start today.

The Mastercourse ‘Data Innovation beyond the hype’ provides pragmatic and industry-oriented sessions on data-driven innovation and AI. Through in-depth webinars, training and workshops, the course addresses the need for companies to innovate their products, services or technology based on the use of data.

Why enroll for this Mastercourse?

The goal of the Mastercourse is to help your business to do more with data. The course cycle consists of six sessions, each focusing on different steps in the data innovation process. In addition, we have developed a set of a topic-specific sessions and webinars focusing on industrial applications of data science and AI.

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  • Session 1: The art of formulating a data science task
  • Session 2: Bring your own data innovation challenge (on-demand)
  • Session 3: The importance of data exploration and hypothesis building
  • Session 4: The power of data visualisation
  • Session 5: The art of feature engineering
  • Session 6: Choosing the right algorithm for the right task 

For whom is this Mastercourse?

The Mastercourse cycle ‘Data innovation beyond the hype’ is open to any entrepreneur interested in developing data and AI solutions, and curious about the opportunities it can offer to industrial companies – including for SMEs.

Product companies
Learn best practices for enhancing your product design, performance, 
and functionality, or to develop additional services using data and AI.
Production companies
Innovate your business by increasing efficiency, improving quality and optimising planning of industrial production processes.
Service companies

Automate and scale up your services through expert advice in data innovation, from feasibility study to proof-of-concept realisation.


Session 6: Choosing the right algorithm

In this webinar session, we will introduce you to the most important data science tasks (classification, clustering, regression, etc.) and provide an overview of the most commonly used algorithms and techniques to solve each of these tasks. For each of the methods, its characteristics, advantages and disadvantages will be explained in order to guide the participants in making a conscious choice in terms of the available data (dimensionality, attribute types, etc.) and the expected model requirements (interpretability, accuracy, scalability, etc.). Finally, the guiding principles to train and evaluate the resulting models, including an overview of common pitfalls and frequently-used evaluation measures, will be presented.

When? 18 and 20 May, 9:30 - 12:00 

Want to dig deeper?
Join our focus sessions!

Focus session 1:
How to leverage data to reliably benchmark asset performance?

In this session, participants will learn about state-of-the-art techniques for analysing fleets of assets, such as industrial machinery or vehicles. The goal of the session is to introduce techniques for solving common problems faced by fleet operators:

  • identifying malfunctioning or underperforming assets
  • dealing with lost data connections and missing data
  • benchmarking assets against one another
  • predicting the remaining useful life of assets
  • modelling new assets that lack historical data

In each case, the fleet context provides additional insights that can help you improve operational efficiency of your assets. Techniques are introduced at conceptual and intuitive level with practical real-world examples.

When? 15 June 2021


Focus session 2:
The industrial relevance of advanced AI/ML methods

The goal of this session is to give participants a better insight into the type of problems that can be tackled using machine-learning techniques. It is illustrated by several real-world examples from a diverse set of domains. Among others, the following machine-learning methodologies will be covered: 

  • Reinforcement learning
  • Deep learning
  • Bio-inspired computing
  • Active learning
  • Federated learning 

For each method, its characteristics, advantages and disadvantages will be explained in more detail, as well as the most commonly used algorithm(s) to solve a particular industrial problem. Participants are guided in making a conscious choice for the appropriate technique in function of the problem setting at hand, as well as the available data (dimensionality, attribute types, etc.) and the expected model requirements (interpretability, accuracy, scalability, etc.). 

Date still to be determined

On-premise training

On demand, we can also give the different sessions at your company’s premises, tailored to your specific data challenges. Or we can provide an intensive training program with one of your colleagues working on your specific data challenges. Interested in one of these alternative training formats?
Pricing and discounts
Sessions Price
Webinars 575 €
Focus sessions 275 €

  • All sessions are given in English.
  • A hardcopy of the course notes is included in the registration price. In case the session is organized as a webinar, access to a digital version of the slides is provided after the session.
With the support of Vlaio (Industriepartnerschap), companies located in Flanders pay only 575 euro when booking and attending at least 2 webinars (1 webinar = 2 sessions) of the Mastercourse webinars. If you attend only 1 webinar, you can apply for KMO-portefeuille support. Both support measures cannot be accumulated. Attendants to the Focus sessions can only apply for the KMO-portefeuille.


In case you are a Flemish SME, it is possible to make use of the KMO-portefeuille. The KMO-portefeuille should be requested at latest 14 days after the course has taken place. (Sirris approval number: DV.O105154). Please note that if you do not apply in time your request will be declined. For more details on the KMO-portefeuille, please visit or contact us through email ( 

General terms and conditions 

Payment of the participation fee for this event or training is subject to Sirris' general terms and conditions. Invoices are to be paid no later than 30 days after the invoice date, VAT included. 

Cancellations are to be made by e-mail ( Cancellations up to 3 working days before the event are free of charge. After this deadline, or in case of a “no show”, the full amount of the registration will be due. Replacement by a colleague is possible if notified in advance. We will be happy to transfer your seat.

For more information, check our general conditions on


Need more details?

Would you like to talk with one of our experts? Or would you like to have some further information on our activities? Then get in touch with us! Our Data Scientist, Mathias Verbeke, will be happy to help.