Course structure and curriculum

Course structure

The two-year master鈥檚 program in Edge Intelligence at Eindhoven University of Technology (黑料福利网) is worth 120 ECTS (European Credit Transfer System) 

FIRST YEAR

You take foundational courses to build a strong foundation. You can choose four electives to deepen your knowledge and explore your interests or broaden your perspective.

SECOND YEAR

During your second year, you can choose from a wide range of electives or you can choose to pursue an external internship to gain off-campus experience, for example at a high-tech company in the Brainport region, one of the Netherlands' top research institutes, or a research lab at a foreign university. For two quarters, a graduation project at one of the research groups of the department emphasizes your further development of independent and high-level academic skills in a professional research environment, always linked to future technologies for society.

Throughout the program, professional and personal development is fully integrated in courses and projects to further train students in becoming skilled, critical and responsible professionals and researchers.

Year 1 Mandatory courses 40 ECTS
  Electives 20 ECTS
Year 2 Electives 20 ECTS (or 5 ECTS electives and 15 ECTS Internship)
  Preparation 10 ECTS
  Graduation Project 30 ECTS

Curriculum

The track emphasizes networked embedded systems, the Internet of Things, and resource-efficient AI at the edge. Core subjects include:

  • Edge Computing
  • Architecture of Distributed Systems
  • Internet of Things
  • Networked Embedded Systems
  • Approximate Computing
  • Intelligent Architectures

Moreover, you can choose from an extensive list of electives to complete your profile:

  • System Validation
  • Advanced Algorithms
  • Automated Reasoning
  • Real - time Systems
  • Massively Parallel Argorithms
  • Cyberattacks, Crime and Defences
  • Advanced Network Security
  • Quantitative Evaluation of Cyber-Physical Systems
  • Electronic Design Automation
  • Multiprocessors
  • Machine Learning for Systems and Control
  • System Design Engineering
  • Embedded Visual Control

Students can also engage in challenge-based projects and graduation assignments with leading research groups and industry partners.