Master’s thesis in Applied Data Science (two year)

Summary

The purpose of the course is for the student to further develop knowledge, understanding, and skills needed to work with problems in the field of computer science in a scientific way. This includes the ability to independently plan, perform and present a project that represents a contribution to current research in the area. The student's knowledge of research methodology shall also be applied in the choice of scientific method and thesis writing.

Admission requirements

  1. Bachelor of Science in computer science or related subjects.
  2. At least 15 credits in programming.
  3. At least 7.5 credits in mathematics.
  4. Knowledge equivalent to English 6 at Swedish upper secondary level.
  5. At least 60 credits completed in the main area of study within the master programme, Computer Science: Applied Data Science
  6. A passing grade in the course Research Methods of Computer Science and Fundamental Computational Theory

Syllabus

Syllabus for students spring 2022

Course Code:
DA638E revision 1
Swedish name:
Examensarbete i applied data science (master, två år)
Level of specialisation
A2E
Main fields of study:
Computer Science
Language:
English
Date of ratification:
02 September 2019
Decision-making body:
Faculty of Technology and Society
Enforcement date:
17 January 2022

Entry requirements

  1. Bachelor of Science in computer science or related subjects.
  2. At least 15 credits in programming.
  3. At least 7.5 credits in mathematics.
  4. Knowledge equivalent to English 6 at Swedish upper secondary level.
  5. At least 60 credits completed in the main area of study within the master programme, Computer Science: Applied Data Science
  6. A passing grade in the course Research Methods of Computer Science and Fundamental Computational Theory

Specialisation and progression relative to the degree regulations

The course is part of the programme Computer Science: Applied Data Science, master’s programme, and can be included in the master's degree in computer science (120 credits).

Purpose

The purpose of the course is for the student to further develop knowledge, understanding, and skills needed to work with problems in the field of computer science in a scientific way. This includes the ability to independently plan, perform and present a project that represents a contribution to current research in the area. The student's knowledge of research methodology shall also be applied in the choice of scientific method and thesis writing.

Contents

The course consists of three parts: problem definition and project planning; the thesis project; and the opposition on another degree project

The thesis project has two phases:

  • To perform the project and document it in writing (in the form of the degree project), and
  • To present and defend the thesis verbally
The opposition consist of carefully studying and critically analysing another student's degree project, producing a written opposition and acting as an opponent in the presentation of another student's degree project.

Learning outcomes

Knowledge and understanding
For a passing grade the student shall be able to:

  • Demonstrate in-depth knowledge of computer science.
Competence and abilities
For a passing grade the student shall be able to:
  • Independently and creatively identify, formulate and handle complex problems
  • Plan and perform research and development projects within predetermined time frames
  • Describe a research project's contribution to an area of knowledge
  • Actively seek and find relevant information on a specific research problem
  • Apply research methods
  • Verbally and in writing present the results of a research project in a scientific manner in international and national contexts.
  • Communicate results of a research project to different target groups
  • Critically analyse a scientific report and identify its main strengths and weaknesses
Evaluation abilities and approach
For a passing grade the student shall be able to:
  • choose a research method for a specific scientific problem and provide arguments as to suitability
  • assess and analyse relevant research issues of importance for data science
  • make data science deliberations based on scientific, societal and ethical aspects
  • demonstrate an insight into the opportunities and limitations of science, the role these play in society and the population’s responsibility for how this is applied
  • demonstrate the ability to identify his or her own need for further knowledge and to take responsibility for his or her own knowledge development.

Learning activities

The teaching is project-based and adapted to the student's previous knowledge, ability, and experience. The main activities are thesis work, supervision and seminars. The student will also present orally and act as an opponent on another thesis.
The supervisor who is assigned to the student (and any external contact person, e.g. a user of the project result) supports and guides the student through the project, but it should be the student who initiates any request for support. The student is expected to report to the supervisor on an ongoing basis during the project work.

Assessments

Students' performance is assessed through:

  • project plan (3 credits, UG),
  • the written degree project and an oral presentation (25 credits, UA),
  • and a public discussion and examination (2 credits, UG).
An A-E passing grade requires a pass in all parts. The final grade is based on the written degree project and the oral presentation.

Grading system

Excellent (A), Very Good (B), Good (C), Satisfactory (D), Pass (E) or Fail (U).

Course literature and other teaching materials

  • Dawson, Christian (2009). Projects in computing and information systems. A student’s guide, 2nd edition. Addison Wesley
  • Oates, B.J. (2005). Researching Information Systems and Computing. Sage Publications, UK
  • Zobel, J. (2004). Writing for Computer Science – The art of effective communication, 2nd edition. Springer, UK
  • Individual literature is selected by the student in consultation with the supervisor

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

Interim rules

When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.

Other Information

The syllabus is a translation of a Swedish source text.

Contact

The education is provided by the Faculty of Technology and Society at the Department of Computer Science and Media Technology.

Further information

Application

17 January 2022 - 05 June 2022 Day-time 100% Malmö This course is offered as part of a program