194.048 Data-intensive Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022S, VU, 2.0h, 3.0EC
TUWEL

Properties

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

Learning outcomes

After successful completion of the course, students are able to

  • identify and solve practical problems of data-intensive computing
  • describe theoretical foundations of distributed data processing
  • apply methods for data processing in distributed data environments
  • apply machine learning to large-scale data in Hadoop/Spark-based cluster environments
  • design solutions for large-scale machine learning und data science problems and tasks
  • develop and deploy data-intensive edge computing strategies

Subject of course

Theory: Map/Reduce, Spark, edge computing, execution graphs
Practical part: Hadoop, Spark, implementation of large-scale data processing and machine learning tasks, edge computing

Teaching methods

Practical implementation of large-scale data processing and machine learning tasks in homogeneous and heterogeneous environments

Mode of examination

Immanent

Additional information


Vorbesprechung/First meeting: March 10th, 14:15, online

Zoom: https://tuwien.zoom.us/j/98214513691?pwd=UWVQZlpqbU8rYVdvckhmbjZmSTg1UT09

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu14:00 - 16:0010.03.2022 - 30.06.2022FAV Hörsaal 1 - INF Lecture
Thu14:00 - 16:0010.03.2022 - 30.06.2022FAV Hörsaal 2 Lecture
Thu14:15 - 15:4510.03.2022 - 30.06.2022 Zoom (see TUWEL)Lecture (online)
Data-intensive Computing - Single appointments
DayDateTimeLocationDescription
Thu10.03.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu10.03.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu10.03.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu17.03.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu17.03.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu17.03.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu24.03.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu24.03.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu24.03.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu31.03.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu31.03.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu31.03.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu07.04.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu07.04.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu07.04.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu28.04.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu28.04.202214:00 - 16:00FAV Hörsaal 2 Lecture
Thu28.04.202214:15 - 15:45 Zoom (see TUWEL)Lecture (online)
Thu05.05.202214:00 - 16:00FAV Hörsaal 1 - INF Lecture
Thu05.05.202214:00 - 16:00FAV Hörsaal 2 Lecture

Examination modalities

Grading based on 3 assignments (A1: 100pt, A2: 100pt, A3: 100pt; Sum 300pt);

ECTS Breakdown:
3.0EC = 75h
7.5 lectures:     15h
Exercise 1:  20h
Exercise 2:  20h
Exercise 3:  20h

Course registration

Begin End Deregistration end
28.01.2022 00:00 09.03.2022 23:59 16.03.2022 23:59

Precondition

The student has to be enrolled for at least one of the studies listed below

Curricula

Study CodeSemesterPrecon.Info
066 645 Data Science 2. Semester

Literature

No lecture notes are available.

Miscellaneous

  • Attendance Required!

Language

English