Pursuant to consolidation Act 778 of August 7, 2019 on Universities (the University Act), the following is established. The programme also follows the Examination Policies and Procedures incl. the Joint Programme Regulations for Aalborg University.
The Master’s programme is organised in accordance with the Ministry of Higher Education and Science’s Order no. 2285 of December 1, 2021 on Full-time University Programmes (the University Programme Order) and Ministerial Order no. 2271 of December 1, 2021 on University Examinations (the Examination Order). Further reference is made to Ministerial Order no. 104 of January 24, 2021 (the Admission Order) and Ministerial Order no. 114 of February 3, 2015 (the Grading Scale Order).
The programme is offered in Aalborg.
The Master’s programme falls under the The Technical Faculty of IT and Design, Aalborg University.
The Master’s programme falls under the Study Board of Electronics and IT.
The programme is affiliated with the Civil engineering corps of external examiners.
Applicants with a legal right of admission (retskrav)
Applicants with the following degrees are entitled to admission:
Applicants without legal right of admission
All applicants without a legal right must prove that their English language qualifications is equivalent to level B (Danish level) in English
The Master’s programme entitles the graduate to the following designations depending on the specialisation:
Specialisation in Network and Distributed Systems:
Specialisation in Artificial Intelligence, Vision and Sound:
The Master’s programme is a 2-year, research-based, full-time study programme. The programme is set to 120 ECTS credits.
The Study Board can approve that passed programme elements from other educational programmes at the same level replaces programme elements within this programme (credit transfer).
Furthermore, the Study Board can, upon application, approve that parts of this programme is completed at another university or a further education institution in Denmark or abroad (pre-approval of credit transfer).
The Study Board’s decisions regarding credit transfer are based on an academic assessment.
The Study Board’s possibilities to grant exemption, including exemption to further examination attempts and special examination conditions, are stated in the Examination Policies and Procedures published at this website: https://www.studyservice.aau.dk/rules
The rules for examinations are stated in the Examination Policies and Procedures published at this website: https://www.studyservice.aau.dk/rules
In the assessment of all written work, regardless of the language it is written in, weight is also given to the student's formulation and spelling ability, in addition to the academic content. Orthographic and grammatical correctness as well as stylistic proficiency are taken as a basis for the evaluation of language performance. Language performance must always be included as an independent dimension of the total evaluation. However, no examination can be assessed as ‘Pass’ on the basis of good language performance alone; similarly, an examination normally cannot be assessed as ‘Fail’ on the basis of poor language performance alone.
The Study Board can grant exemption from this in special cases (e.g., dyslexia or a native language other than Danish).
The Master’s Thesis must include an English summary. If the project is written in English, the summary can be in Danish. The summary is included in the evaluation of the project as a whole.
It is assumed that the student can read academic texts and use reference works, etc., in English.
The following competence profile will appear on the diploma:
A Candidatus graduate has the following competency profile:
A Candidatus graduate has competencies that have been acquired via a course of study that has taken place in a research environment.
A Candidatus graduate is qualified for employment on the labour market based on his or her academic discipline as well as for further research (PhD programmes). A Candidatus graduate has, compared to a Bachelor, developed his or her academic knowledge and independence so as to be able to apply scientific theory and method on an independent basis within both an academic and a professional context.
Knowledge
Skills:
Competences:
The programme is structured in modules and organised as a problem-based study. A module is a programme element or a group of programme elements, which aims to give students a set of professional skills within a fixed time frame specified in ECTS credits, and concluding with one or more examinations within specific exam periods. Examinations are defined in the curriculum.
The programme is based on a combination of academic, problem-oriented and interdisciplinary approaches and organised based on the following work and evaluation methods that combine skills and reflection:
All modules are assessed through individual grading according to the 7-point scale or Pass/Fail. All modules are assessed by external examination (external grading) or internal examination (internal grading or by assessment by the supervisor only).
Offered as:
1-professional | ||||||
Specialisation:
Network and Distributed Systems | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation method | Assessment method | Language |
1 Semester
| ||||||
Communication Systems
(ESNNDSK1P2) | Project | 15 | 7-point grading scale | Internal examination | Oral exam based on a project | English |
Machine Learning
(ESNESK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Dependable and Secure Distributed Systems
(ESNNDSK2K4) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Performance and Reliability Analysis of Communication Networks
(ESNNDSK1K3) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
2 Semester
| ||||||
Reliability, Safety and Security
(ESNNDSK2P2) | Project | 15 | 7-point grading scale | External examination | Oral exam based on a project | English |
Advanced Network Security
(ESNNDSK1K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
2ND SEMESTER ELECTIVE COURSE
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
3 Semester
Option A
| ||||||
AI in the Context of Computer Engineering
(ESNNDSK3P8) | Project | 20 | 7-point grading scale | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSE
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
3 Semester
Option B
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P5) | Project | 20 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSE
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
3 Semester
Option C
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P6) | Project | 25 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSE
CHOOSE 1 COURSE MODULE
| Course | 5 | ||||
3 Semester
Option D
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P7) | Project | 30 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3-4 Semester
Option E
| ||||||
Master's Thesis
(ESNNDSK4P6) | Project | 50 | 7-point grading scale | External examination | Master's thesis/final project | English |
3RD SEMESTER ELECTIVE COURSE
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
4 Semester
| ||||||
Master's Thesis
(ESNNDSK4P5) | Project | 30 | 7-point grading scale | External examination | Master's thesis/final project | English |
2ND SEMESTER ELECTIVE COURSE CHOOSE 2 COURSE MODULES | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation Method | Assessment method | Language |
Deep Learning
(ESNNDSK2K3) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Numerical Scientific Computing
(ESNAVSK2K1) | Course | 5 | Passed/Not Passed | Internal examination | Active participation/continuous evaluation | English |
Networks and Systems
(ESNESK2K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
3RD SEMESTER ELECTIVE COURSE CHOOSE 2 COURSE MODULES | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation Method | Assessment method | Language |
Stochastic Systems
(ESNESK1K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Image Processing and Computer Vision
(MSNAVSK1232) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Perception and Acquisition of Data
(MSNAVSK1231) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Quantum Information and Computing
(ESNESNK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
3RD SEMESTER ELECTIVE COURSE CHOOSE 1 COURSE MODULE | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation Method | Assessment method | Language |
Stochastic Systems
(ESNESK1K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Image Processing and Computer Vision
(MSNAVSK1232) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Perception and Acquisition of Data
(MSNAVSK1231) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Quantum Information and Computing
(ESNESNK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Offered as:
1-professional | ||||||
Specialisation:
Artificial Intelligence, Vision and Sound | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation method | Assessment method | Language |
1 Semester
| ||||||
Computer Vision
(ESNAVSK1P1) | Project | 15 | 7-point grading scale | Internal examination | Oral exam based on a project | English |
Machine Learning
(ESNESK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Perception and Acquisition of Data
(MSNAVSK1231) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Image Processing and Computer Vision
(MSNAVSK1232) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
2 Semester
| ||||||
Acoustics, Sound Processing and Sound Perception
(ESNAVSK2P1) | Project | 15 | 7-point grading scale | External examination | Oral exam based on a project | English |
Deep Learning
(ESNNDSK2K3) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Numerical Scientific Computing
(ESNAVSK2K1) | Course | 5 | Passed/Not Passed | Internal examination | Active participation/continuous evaluation | English |
Fundamentals of Acoustics and Sound
(ESNAVSK2K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
3 Semester
Option A
| ||||||
AI in the Context of Computer Engineering
(ESNNDSK3P8) | Project | 20 | 7-point grading scale | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSES
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
3 Semester
Option B
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P5) | Project | 20 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSES
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
3 Semester
Option C
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P6) | Project | 25 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3RD SEMESTER ELECTIVE COURSES
CHOOSE 1 COURSE MODULE
| Course | 5 | ||||
3 Semester
Option D
| ||||||
Project-Oriented Study in an External Organisation
(ESNNDSK3P7) | Project | 30 | Passed/Not Passed | Internal examination | Oral exam based on a project | English |
3-4 Semester
Option E
| ||||||
Master's Thesis
(ESNNDSK4P6) | Project | 50 | 7-point grading scale | External examination | Master's thesis/final project | English |
3RD SEMESTER ELECTIVE COURSES
CHOOSE 2 COURSE MODULES
| Course | 10 | ||||
4 Semester
| ||||||
Master's Thesis
(ESNNDSK4P5) | Project | 30 | 7-point grading scale | External examination | Master's thesis/final project | English |
3RD SEMESTER ELECTIVE COURSES CHOOSE 2 COURSE MODULES | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation Method | Assessment method | Language |
Stochastic Systems
(ESNESK1K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Dependable and Secure Distributed Systems
(ESNNDSK2K4) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Performance and Reliability Analysis of Communication Networks
(ESNNDSK1K3) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Quantum Information and Computing
(ESNESNK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
3RD SEMESTER ELECTIVE COURSES CHOOSE 1 COURSE MODULE | ||||||
Module name | Course type | ECTS | Applied grading scale | Evaluation Method | Assessment method | Language |
Stochastic Systems
(ESNESK1K2) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Dependable and Secure Distributed Systems
(ESNNDSK2K4) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Performance and Reliability Analysis of Communication Networks
(ESNNDSK1K3) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
Quantum Information and Computing
(ESNESNK1K1) | Course | 5 | 7-point grading scale | Internal examination | Written or oral exam | English |
All students who have not participated in Aalborg University’s PBL introductory course during their Bachelor’s degree must attend the introductory course “Problem-based Learning and Project Management”. The introductory course must be approved before the student can participate in the project exam. For further information, please see Department of Electronics Systems's webiste.
The curriculum is approved by the dean and enters into force as of September 1, 2022.
On February 11, 2022 the Pro-Dean of Education has approved that the form of assessment in the module "Project-Oriented Study in an External Organisation" on the 3rd Semester is changed from 7-point grading scale to Passed/Not Passed as of September 2022.
On April 26, 2022 the Pro-Dean of Education has approved that the the elective module "Advanced Network Security" is replaced with the module "Dependable and Secure Distributed Systems" on the 3rd Semester as of Autumn 2022.
On January 13, 2023 the Pro-Dean of Education has approved that the type of exam in the module "Numerical scientific computing" is changed from written or oral to active participation/continuous evaluation, with oral re-examination as of Spring 2023.
On Febuary 15, 2023 the Pro-Dean of Education has approved the addition of a prerequisite for enrollment for the exam in the modules: "Systems of Systems", "Reliability, Safety and Security" and "Acoustics, Sound Processing and Sound Perception" on the 1st Semester, as of Spring 2023.
The prerequisite is as follows:
On June 7th, 2023, the Pro-Dean of Education has approved the addition of the elective course "Quantum Information and Computing" to the 3th semester.
The amendment is valid from autumn 2023.
On November 12th, 2023, the Pro-Dean of Education has approved that the form of assessment in the module "Fundamentals of Acoustics and Sound" is changed from written to written and oral as of spring 2024.