Programme syllabus autumn 2024
Programme syllabus autumn 2024
Title
Computer Science: Applied Data Science, Master's Program (Two-Year)
Swedish title
Datavetenskap: Tillämpad data science, masterprogram
Programme code
TACAS
Credits
120 credits
Programme establishment date
2019-06-17
Syllabus approval date
2023-05-09
Syllabus valid from
2024-09-02
Decision-making body
Faculty of Technology and Society
Entry requirements
- Bachelor's degree or master's degree (at least 180 credits) in computer science or related topics such as mathematics, informatics, telecommunications, electrical engineering, or physics.
- At least 15 credits in programming.
- At least 7.5 credits in mathematics.
- The equivalent of English 6 at Swedish upper secondary level.
Level
Advanced level
Organisation
The programme deepens the students’ knowledge and skills in computer science and research methods in the field of data science — an emerging interdisciplinary subject at the borderlines between computer science, mathematics and communication. The students will study and apply methods and algorithms that are used by data analysts and engineers working at the forefront of research. The programme covers the entire data management process from data collection,,through to data processing and analysis and ultimately to visualisation and reporting of results. Students will use techniques within a variety of fields such as applied mathematics and statistics, machine learning and cloud services for large data sets. They will translate their knowledge into practice by tackling real-life, data science-related issues and challenges that arise in both the private sector and society at large. In this way, students will build up a repertoire of tools and systems and the ability to determine how to use them to solve specific problems
Semester 1, Autumn 2024
Artificial intelligence for data science
DA631E, 15 credits (compulsory)
Main field of study: Computer Science
Statistical Methods for Data Science
MA660E, 7.5 credits (compulsory)
The course does not have a main field of subject.
Data and Society
DA630E, 7.5 credits (compulsory)
Main field of study: Computer Science
Semester 2, Spring 2025
Exploratory Data Analysis, Visualization and Storytelling
MA661E, 7.5 credits (compulsory)
The course does not have a main field of subject.
Data-Driven Methodologies for Software Development
DA635E, 7.5 credits (compulsory)
Main field of study: Computer Science
Semester 3, Autumn 2025
Research Methods of Computer Science and Fundamental Computational Theory
DA658E, 7.5 credits (compulsory)
Main field of study: Computer Science
Big Data Analytics on Cloud Computing Infrastructures
DA636E, 15 credits (compulsory)
Main field of study: Computer Science
Capstone project in Applied Data Science
DA637E, 7.5 credits (compulsory)
Main field of study: Computer Science
Semester 4, Spring 2026
Master’s thesis in Applied Data Science (two year)
DA659E, 30 credits (compulsory)
Main field of study: Computer Science
Qualitative targets
Knowledge and understanding
In order to complete a master’s degree in Computer Science the student must:
- demonstrate knowledge and understanding of computer science, incorporating broad knowledge within the field as well as substantial, specialised knowledge within certain aspects of the field,
- demonstrate in-depth insight into relevant research and development work; and
- demonstrate in-depth knowledge of methodologies within computer science.
Competencies and skills
In order to complete master’s degree in Computer Science the student must:
- demonstrate the ability to critically and systematically integrate knowledge and to analyse, assess and handle complex phenomena, issues and situations, even with limited information;
- demonstrate the ability to critically, independently and creatively identify and formulate questions, to plan and execute – using appropriate methods – advanced assignments within specific deadlines and thus contribute to the development of knowledge, and to evaluate such work;
- demonstrate the ability in both national and international settings to orally and in writing clearly describe and discuss his/her conclusions and the knowledge and arguments on which these are based, in dialogue with different groups; and
- demonstrate the skills that are required to take part in research and development work or for independent work in other qualified activities.
Evaluation and approach
In order to complete a master’s degree in Computer Science the student will:
- demonstrate the ability within computer science to make assessments in relation to relevant scientific, social and ethical aspects, as well as demonstrating awareness of ethical issues in research and development work,
- demonstrate insight into the opportunities and limitations of the science, the role these play in society and the human responsibility for how this is used, and
- demonstrate the ability to identify their own need for further knowledge and to take responsibility for their own knowledge development.
Degree
Master's Degree (120 credits)
Master's degree with a major in Computer Science (120 credits).
Master of Science in Computer Science (120 credits). A Master of Science in Computer Science is achieved after the student has completed course requirements corresponding to 120 credits, of which all compulsory courses within the programme must be completed with at least a passing grade. In addition, the student must have completed a bachelor’s degree of at least 180 credits (or the equivalent qualification completed abroad)
Additional information
Language of instruction: English
The prerequisites for admission to each individual course are provided in the respective syllabi.
A decision to discontinue a programme will result in the programme syllabus ceasing to be valid. However, students will have the opportunity to complete their studies within the nominal period of study(calculated from the last admission to the programme's first semester) andduring at least the following two semesters, known as the ’discontinuation period’.
This document is a translation of a Swedish source text.