| TNM098 |
Advanced Visual Data Analysis, 6 ECTS credits.
/Avancerad visuell dataanalys/
For:
CS
DAV
MT
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Prel. scheduled
hours: 48
Rec. self-study hours: 112
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Area of Education: Technology
Main field of studies: Media Technology and Engineering
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Advancement level
(G1, G2, A): A
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Aim:
After completing the course the student should be able to:
- Examine new, complex data sets and identify relevant features which might be extracted
- Select and apply advanced algorithmic methods for analysis of large complex data sets to determine valuable results
- Address issues with very large data sets and develop approaches to the 'big data' problem
- Display extracted relevant information from such data sets using standard visualization methods
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Skills in programming and computer graphics programming, mathematics, the course Information Visualization or equivalent.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Organisation:
The course is composed of lectures, laboratory assignments, seminar sessions and a substantial project work.
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Course contents:
This course builds upon the course, Information Visualization, with a focus on the data modelling, mining and analysis techniques with are the foundation of modern visual data analysis methodology. Such methods are becoming very important as the scale of data available for analysis expands, leading to the so-called 'big data' problem affecting business, healthcare, government, science and industry.
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Course literature:
"Principles of Data Mining" by David Hand, Heikki Mannila and Padhraic Smyth.
Relevant scientific articles provided by the lecturers
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Examination: |
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Laboratory work
Project assignment
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1 ECTS
5 ECTS
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Course language is English.
Department offering the course: ITN.
Director of Studies: Camilla Forsell
Examiner: Katerina Vrotsou
Link to the course homepage at the department
Course Syllabus in Swedish
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