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Online Course: Digital Transformation and Servitization in Industrial Manufacturing

France, Paris
Application fee €100 one-time

• Main fee: 100€
• 50% discount for students from Regional Innovation Scheme (RIS) countries and women: 50€
EITM Doctoral School Students: Free

IMPORTANT: The APPLICATION FEE is not reimbursable

More information



*Online Short Course: Digital Manufacturing (18th & 19th October)

The short course will be organized by FEUP (Faculdade de Engenharia da Universidade do Porto), which is one of our partner universities.

The following topic will be delivered by an expert in the short course

•    How is Industry Becoming Digital?
•    From Products to Servitization
•    Servitize Machine Intelligence
•    How to Servitize Machine Learning
•    2 days of Hackathon
•    Hackathon: final presentation

Please find more details in the Program Structure.

The short course will be delivered by 4 speakers who are highly experienced in their respective fields and they will be your supervisors throughout the course

•    Rui Pinto: He received a Master’s degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto (FEUP), and in 2022 a PhD in Computer Engineering from the same school. He is currently an Assistant Researcher at FEUP and an Integrated Member of the Research Center for Systems & Technologies (SYSTEC). Since 2013, as a researcher, he has participated in at least 19 national and European Research and Development projects, mainly focused on the topics of digitization of industrial processes, WSAN, Edge/Cloud Computing, Smart Components, bio-inspired cybersecurity and Education 4.0.

•    Gil Gonçalves: He is an Assistant Professor at the Faculty of Engineering of the University of Porto (FEUP) in the Department of Informatics Engineering (DEI). Gil is the Coordinator of the thematic line SYSTEC- MANUFACTURING in the SYSTEC RD Unit and is responsible for the DIGITAL and InTelligent Industry laboratory. With an extensive experience in research and innovation, Gil has been involved in over 35 National and European RTD projects and studies, as Principal Investigator in many of them, to promote digital transformation in different sectors like manufacturing, health and agri-food.

•   João Reis: João is the Data Science Lead at DEUS, for the past year and a half. Before that, mostly an academic with close to 10 years of research at the University of Porto, with a PhD in AI focusing on novel approaches of Zero-Shot Learning.

•   Eliseu Pereira: Enthusiastic of Internet of Things, Machine Learning, and Data Analytics, Eliseu Moura Pereira is a researcher at the Research Center for Systems & Technologies (SYSTEC) hosted in the Faculty of Engineering, University of Porto (FEUP). He received an M.Sc. in Electrical and Computers Engineering degree from FEUP in 2018 and is a Ph.D. student in Informatics Engineering. He is currently involved in several projects related to Smart Manufacturing, applying concepts of interoperability, reconfiguration, and analytics to Cyber-Physical Production Systems

Participation fees

• Main fee: 100€
• 50% discount for students from RIS* countries and women: 50€
EITM Doctoral School (DS) Students: Free

For EITM DS students, this short course will be part of their I&E Program in year 2.

*Please find the Regional Innovation Scheme (RIS) countries here.

Programme structure

Topics and learning outcomes

1. How is Industry Becoming Digital?

Students will learn about new digital transformation, as a new trend in industrial manufacturing. This session will introduce new digital technologies and how these technologies are driving new industrial solutions.

2. From Products to Servitization

Students will be able to describe what servitization is and enumerate the main benefits and difficulties of moving from products to services. Moreover, students will show the role of servitization in the circular economy, while discussing its impact throughout the historical industrial revolutions and manufacturing paradigms.

3. Servitize Machine Intelligence

Students will analyse and discuss predictive and prescriptive analytic problems that can benefit from servitization. Moreover, students will be presented with a challenge, to be tackled in the hackathon, regarding the usage of anomaly detection and meta-heuristic methods to improve the quality of prescriptive solutions.

4. How to Servitize Machine Learning

Students will identify different machine intelligence tools that rely on servitization, along with platforms and MLOps stacks. Also, students will describe the machine learning lifecycle and relate different machine intelligence tools to the various stages of the lifecycle. Finally, students will define what Jupyter Notebooks are, and explain how they can use it to develop and document software solutions, considering the challenge presented.

5. 2 days of Hackathon

Students will learn and explore the different phases of the Google design sprint; starting in the understand and diverge phases. In these phases, students will analyse how to build a Jupyter Notebook using a collaborative Python IDE, such as Google Collab, and explore strategies to analyse the dataset provided and develop anomaly detection and meta-heuristic methods.

6. Hackathon: final presentation

Students will learn how to present and justify a complex solution to an industrial challenge; mentors will be commenting on the presentation and assessing the students.

For more information, contact us at:


Apply now! Year 2023
Application period has ended
Studies commence
18 Oct 2023
Apply now! Year 2023
Application period has ended
Studies commence
18 Oct 2023
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