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About course

DD2257 Visualization 7.5 credits

Administer About course

The focus of this course is on discussing efficient techniques to visually represent large-scale data sets from simulation and measurement. We will discuss the visualization pipeline, data structures, mapping techniques and special rendering techniques for data from different application domains such as fluid dynamics, climate research, medicine or biology. Various examples will be given to outline the benefits of visualization techniques in practical applications.

Choose semester and course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Application

For course offering

Autumn 2024 visual24 programme students

Application code

50330

Headings with content from the Course syllabus DD2257 (Autumn 2024–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Data structures and algorithms for visualisation of spatio-temporal data sets. Topological data analysis. Feature based methods. Colour. Perception. Fundamental elements of visualization. Software tools for visualization.

Intended learning outcomes

After completing the course with a passing grade the student should be able to:
• name concepts and algorithms in visualization and relate them to one another
• describe the basics of visualization algorithms and concepts
• identify and characterise results of selected visualization algorithms
• apply visualization algorithms to small data sets.

Literature and preparations

Specific prerequisites

  • Knowledge in Calculus in One Variable, 7,5 credits, equivalent to completed course SF1625/SF1673.
  • Knowledge in linear algebra, 7,5 credits, equivalent to completed course SF1624/SF1672/SF1684.
  • Knowledge and skills in programming, 6 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/ DD100N/ID1018.

Recommended prerequisites

The course DH2320 "Introduction to Visualization and Computer Graphics" is recommended.

Equipment

No information inserted

Literature

No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LAB1 - Laboratory Assignments, 3.5 credits, grading scale: P, F
  • TEN1 - Examination, 4.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

TEN1 is conducted as a written exam.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Mathematics

Education cycle

Second cycle

Add-on studies

Please discuss with the instructor.

Contact

Tino Weinkauf, weinkauf@kth.se

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex