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Programme syllabus

Autumn 2021

Programme syllabus, Autumn 2021

Title

Computer Science: Applied Data Science, Master's Program (Two-Year)

Swedish title

Datavetenskap: Tillämpad data science, masterprogram

Programme code

TACAS

Credits

120 credits

Language of instruction

English

Decision-making body

Faculty of Technology and Society

Syllabus valid from

2021-08-30

Programme establishment date

2019-06-17

Syllabus approval date

2020-08-25

Level

Advanced level

Entry requirements

  1. 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.
  2. At least 15 credits in programming.
  3. At least 7.5 credits in mathematics.
  4. The equivalent of English 6 at Swedish upper secondary level.

Programme structure

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

Programme contents

Semester 1, autumn 2021

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)
No main field of study
Data and Society
DA630E, 7.5 credits (Compulsory)
Main field of study: Computer Science

Semester 2, spring 2022

Exploratory Data Analysis, Visualization and Storytelling
MA661E, 7.5 credits (Compulsory)
No main field of study
Data-Driven Methodologies for Software Development
DA635E, 7.5 credits
Main field of study: Computer Science
Advanced Machine Learning
DA633E, 15 credits (Compulsory)
Main field of study: Computer Science

Semester 3, autumn 2022

Research Methods of Computer Science and Fundamental Computational Theory
DA634E, 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
Main field of study: Computer Science

Semester 4, spring 2023

Master's thesis in Applied Data Science (two year)
DA639E, 30 credits (Compulsory)
Main field of study: Computer Science

Learning outcomes

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

The prerequisites for admission to each individual course are provided in the respective syllabi.
This document is a translation of a Swedish source text.