Advanced Academic Studies, 3 credits

Akademiska studier på avancerad nivå, 3 hp


Main field of study


Course level

Second cycle

Course type

Single subject and programme course


Oleg Sysoev

Course coordinator

Oleg Sysoev

Director of studies or equivalent

Ann-Charlotte Hallberg
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Weeks Timetable module Language Campus ECV
F7MSL Statistics and Machine Learning, Master´s Programme 1 (Autumn 2019) 201934-201944 1+3+4 English Linköping, Valla C

Main field of study


Course level

Second cycle

Advancement level


Course offered for

  • Masters Programme in Statistics and Machine Learning

Entry requirements

A bachelor’s degree in one of the following subjects: statistics, mathematics, applied mathematics, computer science, engineering, or equivalent. Completed courses in calculus, linear algebra, statistics and programming are required. 
Documented knowledge of English equivalent to Engelska B/Engelska 6

Intended learning outcomes

After completion of the course, the students should be able to:
- write a disposition of written technical/scientific reports
- summarize scientific publications
- correctly indicate and use citations and references in written reports
- account for the principles of reviewing the technical/scientific reports
- account for the opportunities and limitations of Statistics and research and discuss responsible usage of Statistics
- account for and follow the basic rules and regulations for advanced studies at Swedish universities, especially at LiU. 

Course content

The aim of the course is to prepare the students for advanced academic studies and also to let the students learn the academic culture in general. A basic ambition is to supply essential tools to the students on the master´s level in Sweden. The course should facilitate the transition from the consumption of science to the production of science.

- Academic writing
- Statistics and research, their role in society and responsible usage of statistics
- Review of scientific works
- Constructive criticism
- University rules, organization and ethical rules
- Rules on citation and reference
- Academic culture
- Equal opportunities
- Introduction to LiU
- Library facilities. 

Teaching and working methods

The course has scheduled lectures, seminars and project works. 
Homework and independent study are a necessary complement to the course. Language of instruction: English.


Attendance at least 90% of the lectures and seminars. Written reports on the project works. Detailed information about the examination can be found in the course’s study guide.

Students failing an exam covering either the entire course or part of the course twice are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.


Two-grade scale, U, G

Other information

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. 

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.


Institutionen för datavetenskap
Code Name Scope Grading scale
PRO1 Project 3 credits U, G
There is no course literature available for this course in studieinfo.

This tab contains public material from the course room in Lisam. The information published here is not legally binding, such material can be found under the other tabs on this page.

There are no files available for this course.