Curriculum

Search

Degree: Data-Centric Engineering (LaDData_DDPOL)
Period: 2022-2023

Learning outcomes:

Data-Centric Engineering graduates have a broad spectrum of expertise from applied mathematics to computational statistics and artificial intelligence. Data-Centric Engineering programme provides a solid stepping stone to a career in academia, government, industry, or finance, as well as entrepreneurial skills for establishing startups. In this programme, you will learn about computational techniques and artificial intelligence for analysing and modelling data.
The skills and competencies gained in the programme prepare you for continual learning and for the ongoing transition from software-intensive to data-intensive engineering work.
The students will have

- knowledge about computer science and engineering, machine learning, applied mathematics, and computational statistics;

- skills in computational techniques, mathematical modelling, and computer science for analysing large datasets and methods for designing complex engineering systems;

- ability for uncertainty quantification and risk analysis, pattern recognition, and understanding and modelling interconnections of large-scale systems;

- competences in the theory and practice of data-centric engineering that will enable you to work on multidisciplinary and interdisciplinary projects on, for example, satellite remote sensing or medical imaging;

- a professional network including connections to international research groups at leading universities, large industrial and financial companies, and start-ups.

Computer Vision and Pattern Recognition graduates will specialise e.g. in image processing/analysis and deep learning with applications in, for example, medical engineering and industrial machine vision.


Content:

Facts

  • Degree Master of Science in Technology (M.Sc. Tech.), (Diplomi-insinööri in Finnish)
  • Higher university degree, gives eligibility to apply for scientific doctoral studies
  • Extent 120 ECTS credits

The Master's degree (120 ECTS) consists of advanced specialisation studies in Computer Vision and Pattern Recognition, credit transfer and elective studies. The Master's Thesis and Seminar is included in the advanced specialisation studies.


CourseMinMax
Core studies0,00
Advanced specialisation studies63,00
Completed in other university0,0060,00
Elective studies27,00