Mindestens jedes 2. Wintersemester
5 Credit points
For information on the duration of the modul, refer to the courses of study in which the module is used.
Non-official translation of the module descriptions. Only the German version is legally binding.
Within this module, students learn how to model complex tasks by means of advanced techniques and methods of data analysis. This includes in particular the question how useful information can be extracted in complex settings without a clear specified objective, and how such basic mathematical models with suitable regularisation or prior can be turned towards efficient algorithms and accompanying theoretical guarantees.
Within this module, the focus lies on modern techniques for automated data analysis with a particular focus on its efficient representation, formalisation, and algorithmic realisation. Topics are taken from the recent research literature, touching on aspects such as slow feature analysis, sparse coding and compressed sensing, core vector machines, time series metrics, and Gaussian processes.
Introduction to computer science (such as algorithms and data structures), mathematics, basic knowledge in machine learning or pattern recognition
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In some degree programmes, the module (partial) examination can also be "ungraded" at the student's discretion. A corresponding specification must be made before the module is taken; a subsequent change (graded - ungraded) is not possible. If the ungraded option is selected, it is not possible to use this module for a degree programme in which this module is taken into account in the overall grade calculation.
Module structure: 0-1 bPr, 0-1 uPr 1
In some degree programmes of the Faculty of Technology, the module examination can also be "ungraded" at the student's discretion (see explanations of the module elements and the respective subject-specific regulations). If the ungraded option is selected, it is not possible to use this module for a degree programme in which this module is taken into account in the overall grade calculation.
See below for explanations of this examination (graded examination option).
Portfolio consisting of per default two-weekly exercises or programming tasks and final oral exam (per default 15 minutes). The exercises are based on the content of the lecture and enable students to train and further investigate the topics. It is required that a sufficient percentage of the exercises are successfully completed (per default 50% of the total number of points which can be achieved during a semester). The final oral exam concerns both, the content of the lecture as well as the exercises.
Degree programme | Profile | Recommended start 3 | Duration | Mandatory option 4 |
---|---|---|---|---|
Bioinformatics and Genome Research / Master of Science [FsB vom 30.09.2016 mit Änderungen vom 15.09.2017, 02.05.2018, 04.06.2020 und 31.03.2023] | 1. o. 3. | one semester | Compulsory optional subject | |
Bioinformatics and Genome Research / Master of Science [FsB vom 17.12.2012 mit Änderungen vom 15.04.2013, 15.10.2014, 02.03.2015, 17.08.2015 und Berichtigungen vom 17.11.2014 und 01.12.2015] | 1. o. 2. o. 3. | one semester | Compulsory optional subject | |
Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] | Variante 1 | 3. | one semester | Compulsory optional subject |
Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] | Variante 2 | 3. | one semester | Compulsory optional subject |
Intelligent Systems / Master of Science [FsB vom 27.07.2018 mit Änderung vom 04.06.2020] | 1. o. 2. o. 3. | one semester | Compulsory optional subject | |
Intelligent Systems / Master of Science [FsB vom 17.12.2012 mit Änderungen vom 15.04.2013, 01.04.2014, 15.10.2014, 02.03.2015 und Berichtigung vom 17.11.2014] | 1. o. 2. o. 3. | one semester | Compulsory optional subject | |
Informatics for the Natural Sciences / Master of Science [FsB vom 30.09.2016 mit Berichtigung vom 10.01.2017 und Änderungen vom 15.09.2017, 02.05.2018, 04.06.2020 und 31.03.2023] | 1. o. 2. o. 3. | one semester | Compulsory optional subject | |
Informatics for the Natural Sciences / Master of Science [FsB vom 17.12.2012 mit Änderungen vom 15.04.2013, 01.04.2014, 15.10.2014, 02.03.2015, 01.12.2015 und Berichtigungen vom 01.04.2014, 17.11.2014 und 12.07.2017] | 1. o. 2. o. 3. | one semester | Compulsory optional subject |
The system can perform an automatic check for completeness for this module.