• Course title: Smart Secure ICT and Innovation
• Number of ECTS: 1
• Course code: MA_TECH-4
• Module(s): Smart Secure ICT and Innovation
• Language: EN
• Mandatory: Yes

• Course title: Smart ICT Technologies I
• Number of ECTS: 5
• Course code: MA_TECH-6
• Module(s): Smart ICT Technologies I
• Language: EN
• Mandatory: Yes

• Course title: Technical Standardisation
• Number of ECTS: 3
• Course code: MA_TECH-5
• Module(s): Technical Standardisation
• Language: EN
• Mandatory: Yes

• Course title: Security for Smart ICT I
• Number of ECTS: 2
• Course code: MA_TECH-8
• Module(s): Security for Smart ICT I
• Language: EN
• Mandatory: Yes

• Course title: Security for Smart ICT I
• Number of ECTS: 2
• Course code: MA_TECH-8
• Module(s): Security for Smart ICT I
• Language: EN
• Mandatory: Yes

Upon completion of this course, the student will be able understand how modern and legacy ICT systems are designed and validated.

He will demonstrate the ability to understand modelling techniques to describe the design of such systems and apply basic quality assessment methods (e.g. testing).

The student will be able to identify key technical problems, and will know several classical problem-solving strategies (typical secure cloud-based digital strategy for an enterprise).

The student will be able to understand and improve a roadmap for the efficient identification and implementation of relevant technical standards for digital trust.

 

• Course title: Security for Smart ICT II
• Number of ECTS: 3
• Course code: MA_TECH-9
• Module(s): Security for Smart ICT II
• Language: EN
• Mandatory: Yes

• Course title: Security for Smart ICT II
• Number of ECTS: 3
• Course code: MA_TECH-9
• Module(s): Security for Smart ICT II
• Language: EN
• Mandatory: Yes

Upon completion of this course, the student will be able to understand the principles of AI and more specifically of machine- learning, including the metrics used to assess machine-learning based solutions.The student will be able to identify the category of algorithms to apply, how to set up a process to integrate and update a machine-learning model into a software system and to assess the level of confidence in the deployed machine learning system.The studied use cases can be any data-intensive system (e.g. IoT,Industry 4.0, smart grid, but also web apps).The student will be able to understand and improve a roadmap for the efficient identification and implementation of relevant technical standards for digital trust. 

• Course title: Smart ICT Technologies II
• Number of ECTS: 5
• Course code: MA_TECH-7
• Module(s): Smart ICT Technologies II
• Language: EN
• Mandatory: Yes

• Course title: Smart ICT Technologies II
• Number of ECTS: 5
• Course code: MA_TECH-7
• Module(s): Smart ICT Technologies II
• Language: EN
• Mandatory: Yes

1. understand the latest advances in Smart ICT technologies;

2. design and implement some advanced Smart ICT concepts;

3. identify existing technical standards and ongoing standardisation activities for the latest advances in Smart ICT technologies.

• Course title: Master Thesis
• Number of ECTS: 30
• Course code: MA_TECH-14
• Module(s): Master Thesis
• Language: EN
• Mandatory: Yes

• Course title: Master Thesis
• Number of ECTS: 30
• Course code: MA_TECH-14
• Module(s): Master Thesis
• Language: FR
• Mandatory: Yes