Curriculum for the Master of Applied Statistics, 2026

1: Preface

Pursuant to consolidation Act 391 of April 10, 2024 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.

2: Basis in Ministerial orders

The Professional Master’s Degree programme is organised in accordance with the Ministry of Higher Education and Science’s Order no. 19 of January 9, 2020 on Professional Master’s Degree Programmes, Ministerial Order no. 2272 of December 1, 2021 on Part-time University Programmes (the Part-Time Order) with subsequent change, and Ministerial Order no. 2271 of December 1, 2021 on University Examinations (the Examination Order) with subsequent change. Further reference is made to Ministerial Order no. 1125 of July 4, 2022 (the Grading Scale Order).

3: Campus

The programme is offered in Aalborg.

4: Faculty affiliation

The Master’s programme falls under The Faculty of Engineering and Science, Aalborg University.

5: Study board affiliation

The Master’s programme falls under Study Board of Mathematical Sciences.

6: Affiliation to corps of external examiners

The Master’s programme is associated with the external examiners corps on Civil engineering corps of external examiners.

7: Admission requirements

Admission to the master programme requires that the applicant has completed a relevant qualifying programme.

Relevant qualifying programmes are:

  • A relevant Bachelor's degree, for example: Bachelor of Engineering, Bachelor of Science within any field of engineering or science; Bachelor of Social Science; Bachelor of Arts.
  • A relevant professional Bachelor's degree / medium-length higher education
  • A relevant medium-term higher education.
  • A relevant diploma course completed as a regulated course.

Furthermore, admission requires that the applicant has 2 years of relevant work experience after completion of the qualifying programme.

Relevant work experience includes, e.g., tasks witin: 

  • Quantitative methods
  • Data processing
  • Data analysis / Business analysis
  • Quality control
  • Programming

Aalborg University may allow admission to applicants who do not fulfil the admission requirements but who are considered to have the necessary prerequisites to accomplish the study programme. The requirement of relevant professional experience cannot be exempted.

8: The programme title in Danish and English

The Master’s programme entitles the graduate to the Danish designation Master i anvendt statistik. The English designation is: Master of Applied Statistics.

9: Programme specifications in ECTS credits

The Master’s programme is a 2-year, research-based, part-time study programme. The programme is set to 60 ECTS credits.

10: Rules concerning credit transfer (merit), including the possibility for choice of modules that are part of another programme at a university in Denmark or abroad

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.

11: Exemption

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

12: Rules for examinations

The rules for examinations are stated in the Examination Policies and Procedures published at this website:https://www.studyservice.aau.dk/rules

13: Rules concerning written work

The Study Board may determine whether, and to what extent, a student's language proficiency is included in the assessment of an individual exam.

Spelling and writing skills are always a part of the assessment of final exams (bachelor’s project, final project, and master’s thesis).

The evaluation is based on an overall assessment, meaning that the student's language proficiency in final exams is assessed both in the written project report and during the oral examination.

The Study Board may, in special cases (e.g., in cases of dyslexia or if the student's native language is not Danish), grant an exemption from the requirement that spelling and writing skills be included in the assessment, unless these skills are an essential part of the exam’s objectives.

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.

14: Requirements regarding the reading of texts in a foreign language

It is assumed that the student can read academic texts in Scandinavian languages as well as in English and use reference works etc. in other European languages.

Furthermore, it is assumed that the student has written and oral command of English, sufficient to participate in online group discussions.

15: Competence profile on the diploma

A Master has competencies that have been acquired through a course of study based on an integration of research results and practical experience.
A Master is able to fulfil highly qualified functions in business, institutions and the like, through scholarship-based personal and academic competencies.

16: Competence profile of the programme

Applied statistics is understood in a broad sense and also includes machine learning, AI, data science, and programming.

Knowledge:

  • Must understand and on a scientific basis reflect on professional knowledge in the field of applied statistics and identify scientific problems in the field of applied statistics
  • Must have knowledge in the field of applied statistics based on research in the field of applied statistics

Skills:

  • Must have skills in methods and tools in the field of applied statistics as well as general skills associated with development, realisation and analysis of solutions
  • Must be able to estimate and choose among theories, methods, tools and general skills and on a scientific basis present new analysis and solution models
  • Must have skills in communicating knowledge and discuss professional and scientific problems with experts and non-experts

Competences:

  • Must have competences to identify and describe a professional problem as well as to highlight this by analysis of relevant data
  • Must have competences to autonomously initiate and implement professional and multidisciplinary collaboration and take on the professional responsibility of such
  • Must have competences to autonomously take the responsibility for own professional development and specialisation

17: Structure and Contents of the programme

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:

  • lectures
  • classroom instruction
  • project work
  • workshops
  • E-Learning
  • exercises (individually and in groups)
  • self-study
  • teacher feedback
  • reflection
  • portfolio work

18: Overview of the programme

Offered as: 1-professional
Module name Course type ECTS Applied grading scale Evaluation method Assessment method Language
1 Semester
Programming for Data Wrangling and Visualisation
(26MASDATAWC1)
Course 5 Passed/Not PassedInternal examinationOral exam English
Introduction to Statistics
(26MASSTATSC2)
Course 5 7-point grading scaleInternal examinationOral exam English
Introduction to AI Techniques
(26MASAITECC3)
Course 5 Passed/Not PassedInternal examinationOral exam English
2 Semester
Elective projects Projekt 15
3 Semester
Advanced Data Wrangling and Interactive Visualisation
(26MASADWIVC4)
Course 5 7-point grading scaleInternal examinationOral exam English
Advanced Statistics
(26MASADSTAC5)
Course 5 Passed/Not PassedInternal examinationOral exam English
Advanced AI
(26MASADVAIC6)
Course 5 Passed/Not PassedInternal examinationOral exam English
4 Semester
Master Project
(26MASMASTER)
Project 15 7-point grading scaleExternal examinationMaster's thesis/final project English

 
Elective projects
Module name Course type ECTS Applied grading scale Evaluation method Assessment method Language
Statistical Modelling of Your Own Data
(26MASP1-1)
Project 15 7-point grading scale External examination Oral exam based on a project English
Applications of AI on Your Own Data
(26MASP1-2)
Project 15 7-point grading scale External examination Oral exam based on a project English

19: Additional information

20: Commencement and transitional rules

The curriculum is approved by the dean and enters into force as of 1 February 2026.

21: Amendments to the curriculum and regulations