Capstone project in Applied Data Science

Summary

The purpose of this project course is that the student prepares for professional life by combining and applying skills and concepts from previous parts of the programme and deepens his or her knowledge in the data science field through project work.

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. Passing grade in the course Data and Society

Syllabus

Syllabus for students autumn 2021

Course Code:
DA637E revision 1.1
Swedish name:
Fördjupningsarbete i tillämpad data science
Level of specialisation
A1F
Main fields of study:
Computer Science
Language:
English
Date of ratification:
26 August 2019
Decision-making body:
Faculty of Technology and Society
Enforcement date:
30 August 2021
Replaces Syllabus ratified:
02 September 2019

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. Passing grade in the course Data and Society

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 project course is that the student prepares for professional life by combining and applying skills and concepts from previous parts of the programme and deepens his or her knowledge in the data science field through project work.

Contents

The course contains the following elements:
The students work in a group to develop a data processing artifact and document their work in a concise project report, as well as giving an oral presentation of the work. The students take on a real-world problem formulated by a faculty member or an industry partner outside of the university, or a topic of their own choice. Particular emphasis is placed on aspects related to project work and project management.

Learning outcomes

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

  • Demonstrate in-depth knowledge within a specific part of data science
Competence and abilities
For a passing grade the student shall be able to:
  • Use scientific work in an advanced project
  • Plan and perform an advanced project within predetermined time frames
  • Apply abilities in all parts of data processing
  • Demonstrate the ability to, in both national and international contexts, verbally and in writing, describe and discuss conclusions, knowledge and arguments relating to the project work, in dialogue with different groups.
  • Work together in teams and lead projects
Evaluation abilities and approach
For a passing grade the student shall be able to:
  • Critically review work within the selected field of study.
  • Identify his or her own need for further knowledge in the selected field and be responsible for his or her own continued learning

Learning activities

Lectures, seminars, project work.

Assessments

Requirements for pass: the course is assessed through:

  • A project report (6.5 credits, UA),
  • An oral presentation and a public discussion and examination (1 credit, UG).
An A-E passing grade requires that all parts have been completed and passed. The final grade is based on the project report.

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
  • Students choose additional literature in consultation with the teachers.

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

08 November 2021 - 16 January 2022 Day-time 50% Malmö This course is offered as part of a program