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Algorithms for Data Analysis

Lecturer Prof. Dr. Petra Mutzel
Module MA-INF 1105
eCampus eCampus
BASIS Link2Basis
Credits 6 CP


We will explore advanced techniques for the design and the analysis of algorithms for data analysis and big data. We will focus on selected examples from classical as well as modern algorithmics. Our discussion will include both polynomial time and exponential time exact algorithms, as well as approximation algorithms for combinatorial optimization problems (often on graphs) and their analysis.

Topics will include algorithms and their analysis for graph similarity (e.g., (sub)graph isomorphism, Weisfeiler-Leman), efficient centrality computation for (time-dependent) networks, streaming algorithms, I/O efficient algorithms, and data structures such as, e.g., Fibonacci heaps, Union-Find, (Cuckoo) Hashing, and their analysis.

Note that knowledge of foundations of algorithms and data structures is essential as prerequisite.


Subject When Where Start Lecturer
Lectures Tuesday 12-14 Online via Zoom 12.10.2021 Prof. Dr. Petra Mutzel
Exercises Wednesday 16-18 Seminarraum 2.050, Friedrich-Hirzebruch-Allee 8 20.10.2021 Philip Mayer, Lutz Oettershagen
Exercises Thursday 10-12 Online via BBB 21.10.2021 Philip Mayer, Lutz Oettershagen

Please see eCampus for the Zoom and BBB link to the lecture and exercises.


The lectures are accompanied by tutorials conducted by Philip Mayer and Lutz Oettershagen. There are two alternative appointments. You only need to attend one of the appointments. One of the appointments will be in presence and one online via BigBlueButton.

The assignment of the attendees is done via TVS. Registering is possible from Friday 15.10 until Monday 18.10. You will need a password for the registration which will be announced when the registration period starts.


You need to actively participate in the exercises as a prerequisite for getting admission for the exams (the offical admission requirements can be found here: link). The exams will be oral (if the number of participants is small enough (t.b.a)) and written otherwise.

teaching/ws2122/da.txt · Last modified: 2021/10/12 17:05 by lutz.oettershagen

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