Database Technology, 6 credits

Databasteknik, 6 hp


Main field of study

Computer Science

Course level

Second cycle

Course type

Single subject and programme course


Olaf Hartig

Course coordinator

Olaf Hartig

Director of studies or equivalent

Patrick Lambrix
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Weeks Timetable module Language Campus ECV
F7MSL Statistics and Machine Learning, Master´s Programme 3 (Autumn 2020) 202045-202102 1 English Linköping, Valla E

Main field of study

Computer Science

Course level

Second cycle

Advancement level


Course offered for

  • Masters Programme in Statistics and Machine Learning

Entry requirements

  • Bachelor's degree equivalent to a Swedish Kandidatexamen of 180 ECTS credits in one of the following subjects:
    • statistics
    • mathematics
    • applied mathematics
    • computer science
    • engineering
  • Completed courses in
    • calculus
    • linear algebra
    • statistics
    • machine learning
    • programming
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6/B)
    (Exemption from Swedish)

Intended learning outcomes

After the completion of the course you should on an advanced level be able to:
 - explain and use the most important terminology within databases and database technology in a correct way 
- design a data model using EER diagrams. 
- design, implement and use a relational database. 
- explain the theory behind the relational model and how this affects good design of databases. 

Course content

The aim of this course is to give a thorough introduction to:
- the theoretical and practical issues underlying the design and implementation of modern database systems
- principles for general database management systems: DBMS, 
- methods for database design and use. 
- datamodelling with EER, Relational databases, Datastructures for databases, SQL, Relational algebra, query optimization, transactions, serialisation, concurrency.

Teaching and working methods

The course consists of lectures and laboratory work. Lectures are devoted to theory and techniques. Database design and implementation techniques are practised in the laboratory work.
Homework and independent study are a necessary complement to the course. Language of instruction: English. 



Written examination. Laboratory work.
Detailed information about the examination can be found in the course’s study guide. 




Institutionen för datavetenskap
Code Name Scope Grading scale
LAB1 Laboratory work 3 credits EC
TENT Examination 3 credits EC
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