186.868 Visual Data Science
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019W, VU, 2.0h, 3.0EC
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Learning outcomes

After successful completion of the course, students are able to

  • employ techniques from visualisation and visual analytics for the exploratory data analysis,
  • employ techniques from visualisation and visual analytics for data presentation,
  • employ strategies from human-computer-interaction (HCI) and perception to improve visualizations, and
  • understand the differences between current software libraries and applications for data science.

There is also a possibility to analyze your own data.

Subject of course

  • The lecture part will start with a theoretical introduction to visualisation, visual analytics and human-computer interaction (HCI).
  • Afterwards practical applications of visualization in data science will be discussed.
  • The lecture also contains a review on the differences between current software applications for data science.
  • In the lab part students will get to know the differences between statistical and visual data analysis.
  • Students will also directly compare different applications, and create a dashboard for the presentation of data analysis results.

Teaching methods

Lecture with slides, programming examples, and live demos

Mode of examination

Immanent

Additional information

Further information can be found at the lecture webpage (https://www.cg.tuwien.ac.at/courses/VisDataScience/).

ECTS-Breakdown:
3 ECTS = 75 working hours, of which
  55 working hours (73%) are meant for the lab part, and
  20 working hours (27%) are meant for the lecture part

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed11:00 - 13:0002.10.2019Seminarraum FAV 05 (Seminarraum 186) Lecture information
Wed11:00 - 13:0009.10.2019HS 14A Günther Feuerstein Lecture 01
Wed11:00 - 13:0016.10.2019 - 11.12.2019FAV Hörsaal 1 - INF Lecture 02-09
Wed11:00 - 13:0018.12.2019HS 14A Günther Feuerstein Lecture 10
Visual Data Science - Single appointments
DayDateTimeLocationDescription
Wed02.10.201911:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture information
Wed09.10.201911:00 - 13:00HS 14A Günther Feuerstein Lecture 01
Wed16.10.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed30.10.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed06.11.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed13.11.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed20.11.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed27.11.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed04.12.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed11.12.201911:00 - 13:00FAV Hörsaal 1 - INF Lecture 02-09
Wed18.12.201911:00 - 13:00HS 14A Günther Feuerstein Lecture 10

Examination modalities

Students can select one of two evaluation models (more information can be found on the lecture website: https://www.cg.tuwien.ac.at/courses/VisDataScience/). Evaluation is done based on the model selected.

Course registration

Begin End Deregistration end
02.10.2019 11:00 20.11.2019 23:59 20.11.2019 23:59

Registration modalities:

Registration can be done via TISS or TUWEL.

Curricula

Literature

No lecture notes are available.

Previous knowledge

  • Data Science basics
  • Programming skills
  • Preferrable knowledge about visualisation

Accompanying courses

Continuative courses

Miscellaneous

Language

English