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Overview

Workload: SWS : 2, Credits 4

Participants: Min: 1 Max: 12 Erwartet: 12

Course type : Seminar

Language: english

Examination date: TBA

Materials

The slides are available here.

You can download the dialog settings workflow here.

Content

This seminar accompanies the lecture "Introduction to Data Analysis" and aims to deepen the understanding of modern data analysis algorithms. This year we will focus on distributed approaches an each participant will investigate how a particular model-searching, sequential algorithm can be optimized for parallel execution under different constraints (limited communication, limited local storage, fragmented data access, streaming data only, ...). Throughout the semester, students will meet in an informal setting to discuss their progress. At the end of the seminar, participants will present their findings and summarize them in a short report. The main output of the seminar 

will be a well written and documented implementation along with the required documentation and performance analysis. 

Literature

Although we will provide suggestions for algorithms, students are also encouraged to bring ideas for algorithms to the first session.

Prerequisites

Successful completion of "Introduction to Data Analysis" or taken in parallel during the semester. 

Java skills are highly recommended.