How to formulate your data science task?

While today's attention mainly goes to examples by major internet companies such as Google, Amazon or Facebook, data science might be even more relevant in other industrial domains and is definitely relevant for SMEs as well. During our mastercourse we give you the details! 

Data innovation allows to derive new insights from experimental data, to profile products and customers, to optimise production processes, to predict failure of machines or even to build data-centred start-ups. In this context the Data and AI Competence Lab of Sirris (EluciDATA Lab) has developed the mastercourse cycle 'Data Innovation beyond the Hype', which consists of six sessions providing a pragmatic and industry-oriented approach to data-driven innovation.  

The first session focuses on 'The art of formulating a data science task'. The goal of this session is to offer an overview of data science and its opportunities for innovation from an industrial point of view. By means of actual cases from current data innovation projects in several domains, the iterative and creative path from business understanding to data exploitation will be described by means of the different steps in the data science workflow. Particular attention will be given to the kind of challenges that can be tackled, and the data and skills that you need to have available in order to realise those challenges. Furthermore, some common beliefs about data analytics as a commodity are debunked. 

Do you want to learn more about data innovation and its opportunities for innovation? Check out and register for our first session on 'The art of formulating a data science task': Session 1.