MSE Master of Science in Engineering

The Swiss engineering master's degree

Each module contains 3 ECTS. You choose a total of 10 modules/30 ECTS in the following module categories: 

  • 12-15 ECTS in technical scientific modules (TSM)
    TSM modules teach profile-specific specialist skills and supplement the decentralised specialisation modules.
  • 9-12 ECTS in fundamental theoretical principles modules (FTP)
    FTP modules deal with theoretical fundamentals such as higher mathematics, physics, information theory, chemistry, etc. They will teach more detailed, abstract scientific knowledge and help you to bridge the gap between abstraction and application that is so important for innovation.
  • 6-9 ECTS in context modules (CM)
    CM modules will impart additional skills in areas such as technology management, business administration, communication, project management, patent law, contract law, etc.

In the module description (download pdf) you find the entire language information per module divided into the following categories:

  • instruction
  • documentation
  • examination 
Intelligent and Hyperconnected Machine (FTP_SmartMach)

Students learn and experience an advanced approach to designing an autonomous real-time process monitoring system (cyber-physical system)



  • General mechanics
  • IT basics 


Learning Objectives

Students learn and experience an advanced approach to designing an autonomous real-time process monitoring system.

This will allow them to experience a development project by directly integrating an expert reflection on the digital autonomy expected of automated mechanisms in the Industry 4.0 world.

They will also be introduced to the multidisciplinary roles that the engineer-designer of tomorrow will have to play in the face of the challenges of digitization and the advent of intelligent and autonomous machines.

This course uses as a red thread the Micro5 eco-demonstrator developed in the framework of the HES-SO thematic programs (2013-2016) and recently equipped with an original and very advanced cognitive system.

Contents of Module

The learning objectives are to allow the student to develop a critical sense and to experience the steps and difficulties related to defining and developing an artificial intelligence system on a production tool.

The following steps will be covered:

  • Positioning and role of the engineer-designer in the face of digitalization issues
  • Definition of a digital cognitive system (prospective and decision-making capacities)
  • Goals to be achieved by the system being developed (issues and methods)
  • Definition of the tools to be developed
  • Development of a relevant cyber-physical system in production (choice of relevant data, signal processing, documentation and data feedback, real-time management, data storage)
  • Data processing and analysis
  • Experimentation through monitored and precursor machining (visualization, experience report)
  • Digitalisation of know-how (empowerment tools)
  • Development of a digital behavioral twin


Teaching and Learning Methods


  • Cognitive system (what and how)
  • Prospective capabilities
  • Cyber-physical system
  • Data feedback and analysis


  • Application to machines
  • Case studies


  • Machining with data feedback
  • Labeling
  • Analyses
  • AI restitution


Download full module description