Programme covers a range of timely, industry topics relevant to modern fields of engineering, comprising competences from electrical engineering, automation, programming, communications, data science, artificial intelligence and machine learning, network security and Internet of Things.

Students will acquire competences in a range of techniques covering the broad areas of mathematics, modelling and analysis of signals and systems, electronics, data science, artificial intelligence, security, networks and distributed systems.

During their studies, students will further acquire expertise in other areas, such as project planning and management, teamwork and coordination, entrepreneurship, critical thinking and sustainability. The Programme will empower students to solve industry-relevant problems employing cutting-edge tools of artificial intelligence, automation and control theory, data analytics, network security, wireless systems, distributed systems and signal processing. Students will be trained in the design and analysis of machine learning models and communication systems, advance their knowledge in the broad field of computer networks and cybersecurity, and gain professional experience through tailored industry-relevant projects and entrepreneurship trainings.

The expertise gained through the Programme features diverse programming skills, good mathematical background, goal-oriented problem solving, as well as efficient project planning and management. 

In particular, students will boast competences in:

• emerging communication technologies: students will learn from experts in the domain of communication and networking;
• cutting-edge automation competences: the Programme boasts theoretical skills and practical expertise at the interconnection between communications and data science;
• emerging information technologies: students will learn from experts in evolving information technologies that define the future in industry and society;
• network security: security is the weak spot in many contemporary technologies, so students will learn to lead the transition of the industry towards security and privacy by design and by default in all types of networks, and more specifically in IoT;
• distributed computer networks: distributed systems have become the norm and are ubiquitously deployed through IoT, so students will learn to command the tools to manage future distributed networks of an unprecedented scale;
• artificial intelligence in networking: data science has found its place in many areas of engineering in recent years and is increasingly dominating also networking domains, students being trained to possess a broad range of tools to structure and analyse huge data sets and to extract meaning from patterns, as well as to appreciate the value created by collecting, communicating, coordinating and leveraging the data from connected devices;
• programming skills: students will gather practical programming expertise in a range of industry-relevant languages;
• project and team working: students will collect practical experience through projects in relation with industry.

The Programme will be structured into 2 years:

• Year 1: basic studies common in student’s home university:
  • General studies (languages, soft skills, …)
  • Mathematics/Programming/Security
  • Communications
  • Data Science
• Year 2: specialization studies, specific to all Partners, Project and Thesis
  • Communications, Data Science, and Security (Grenoble INP)
  • Communications and Data Science (Técnico Lisboa)
  • Communications, Automation and Machine Learning (Aalto University)
  • Communications, Machine Learning, Medical Informatics & Biomedicine (TU Braunschweig)
  • Communications, 5G/6G and Internet of Things, and Data Science (UPC)

All Consortium Universities can be either Home or Host University. In Year 1, students complete courses with 60 ECTS at Home University. In Year 2, students either:

• Option A: Student completes courses with 30 ECTS and the thesis with 30 ECTS in one Host University
• Option B: Student completes courses with 30 ECTS in Host University 1 in the autumn semester and the thesis with 30 ECTS in Host University 2 in the spring semester

Option B is targeted only for the students who are residents in the Home or Host University country at the enrolment to the programme (Erasmus Mundus regulation).

Code: ELEC3067
Credits: 90 ECTS
Responsible professor: Stephan Sigg
Other professors involved: Stephan Sigg, Ville Kyrki, Alexander Jung

Entry year in Aalto University

Exit year in Aalto University

Elective studies

NOTE: Only second year studies are offered at this university.
This is a preliminary curriculum and is subject to change.
Students may choose 30 ECTS worth of courses from the following tracks:

Cloud Computing & Data Infrastructures track:

Mandatory (18 ECTS)

•  Large-Scale Data Management (6 ECTS - 36h)
• Cloud Computing, From Infrastructures to Applications (6 ECTS - 36h)
• Information Security (3ECTS - 21h)
• Advanced Computer Science Topics (3ECTS - 24h)

Specialization (Choose 12 ECTS)

• Next Generation Software Development (3 ECTS - 18h)
• Process Engineering (3 ECTS - 18h)
• Distributed Systems (3ECTS - 18h)
• Virtualization (3 ECTS - 18h)
• Scientific methodology and performance evaluation (3 ECTS-18h)
• Advanced Data Networks (6ECTS - 36h)
   

Optional (3 ECTS)

Your may replace 3 ECTS from the Specialization list, by one of the lectures below:

• Artificial Intelligence Project
• Models and languages for model checking
• Information Visualization

Applied AI and Interactive Systems:

• Natural Language Processing and Information Retrieval (6 ECTS - 36h)
• Computer Vision (6 ECTS - 36h)
• Human-Computer Interaction (6 ECTS - 36h)
• Robotics (6 ECTS - 36h)
• Computer Graphics (6 ECTS - 36h)
• Large-Scale Data Management (6 ECTS - 36h)
• Information Visualization (3 ECTS - 18h)
• Multi-Agent Systems (3 ECTS - 18h)
   

Students who have chosen this theme, have the possibility to replace 6 ECTS from the list above with courses from the Specialization block only of Cloud Computing & Data Infrastructures theme.

Students will complete their Master’s Thesis (M.Sc.) for a total of 30 ECTS. Students should complete a total of 60 credits. 

Entry year in Técnico Lisboa

Please check the up to date curriculums from partner University's own website.

Exit year in Técnico Lisboa

Entry year in TU Braunschweig

Please check the up to date curriculums from partner University's own website.

Exit year in TU Braunschweig

Electives List

Please check the up to date curriculums from partner University's own website.

* As an elective it is only available in first year of studies
** A total of 120 credit points must be earned to successfully complete the programme. In addition to the 30-credit Master's thesis module, at least 60 credit points must be earned through graded modules that require an examination (not just a course achievement!).

Entry year in UPC

Please check the up to date curriculums from partner University's own website.

Exit year in UPC