Joe Steinhauer
Senior Lecturer in Computer Science
School of Informatics
Information Fusion A1F
Course, Master's (2nd cycle),
7.5 credits,
IT729A
Application
Choose a course instance to see course syllabus and admission requirements.
Autumn 2022, Location: Skövde, Pace of study: 50%
Application
Application is done after nomination.
Course syllabus, with reading list
When? Where? How?
Study period: 31 October 2022 - 15 January 2023
Location: Skövde, Campus, Daytime
Pace of study: 50%
Admission Requirements
Prerequisite courses for this course are: Passed courses: IT733A-Artificial Intelligence A1N (or the equivalent).
Selection
Guaranteed admission.
Language
The courses are conducted in English.
This course is for you who want to gain knowledge within the research area information fusion and the different methods and techniques that are used to fuse information (data) from different sources with the purpose to support human decision making in different application areas. The information that has to be fused is often subject to different types of uncertainty (missing data, wrong or noisy data). Therefore, uncertainty handling is an important part of information fusion. Within this course different methods for uncertainty handling are discussed.
If you study data science, computer science, information technology or informatics, you will get an overview of the area of information fusion, gain knowledge about several different methods used for information fusion. You also learn how information fusion can be used within decision support systems and how uncertainty can be handled. Furthermore, the course discusses the user’s role in the team of information fusion/decision support system and user.
