offered at least annually
10 Credit points
For information on the duration of the modul, refer to the courses of study in which the module is used.
By completing the module, students acquire the following skills:
They understand advanced theoretical and methodological concepts of machine learning (ML) and data mining at an appropriate level for the Master's degree. They know basic and advanced methods for analyzing complex data structures, for automated feature selection, for modeling under uncertainty and for extracting information from large amounts of data.
Students are able to structure challenging problems, select and combine suitable learning architectures and data mining methods and apply them to complex scenarios in a methodologically sound manner. They can systematically compare and evaluate different modeling approaches and transfer them to new problems or data contexts. In addition, they are able to transfer existing knowledge from the fields of ML and data mining to new areas of application or integrate findings from one of these areas into the other.
In this module, students deal in depth with fundamental and current topics in machine learning and data mining.
The subject matter includes basic and advanced theoretical, methodological and algorithmic concepts for data-driven modeling, pattern recognition and structure discovery in large amounts of data. Topics covered can include complex learning architectures, probabilistic models, reinforcement learning methods and advanced approaches to automated data analysis. In addition, in-depth theoretical aspects and efficient algorithmic methods could be discussed.
The specific content of the module is determined by the courses chosen by the students. The choice from available courses is based on personal interest.
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The module is to be studied as follows:
First, students attend an introductory course (lecture or seminar) and an accompanying course (seminar or exercise), whereby the combination of seminar + seminar is excluded.
Subsequently, a first partial examination is taken. The requirements are determined by the selected course types.
In the following semester, an in-depth element in the same or a closely related subject area is studied (in-depth project, in-depth exercise, in-depth exercise (alternative) or in-depth seminar).
Alternatively, a second topic can be studied in depth, building on the first part (lecture on the second topic + exercise on the second topic). In the latter case, all courses are usually offered by the same teacher and build on each other in terms of content. The type of the subsequent second part of the examination depends on the chosen combination of course elements.
The total number of credits for the courses to be attended is 8.
The total number of credits for the two parts of the examination is 2.
Module structure: 2 bPr 1
dies ist eine Alternative zur Übung mit einer Kontaktzeit von 30h
Diese vertiefende Übung baut auf die einführenden Veranstaltungen des Moduls auf.
Diese vertiefende Übung baut auf die einführenden Veranstaltungen des Moduls auf.
Partial examination 1
Upon completion of module partial examination 1 with EITHER the introductory lecture + exercise OR introductory seminar + exercise.
Portfolio with final examination consisting of:
1) Portfolio of exercises on the content of the introductory lecture/seminar
Exercise tasks or programming tasks related to the course (pass mark 50% of the achievable points). The assessment of the exercise tasks also includes direct questions about the solution approaches, which must be answered by the students in the exercises. The lecturer may require individual explanations and demonstrations of tasks and may replace some of the exercises with classroom exercises. The exercises in the portfolio are usually assigned on a weekly basis and serve to accompany the independent implementation of the learning content presented in the seminar/lecture.
2) A final examination on the introductory lecture OR the introductory seminar
The final examination on the content of the seminar/lecture refers to the exercise or programming tasks or is based on the skills learned in the exercises.
Further details, in particular regarding the duration of the final examination, can be found in the course description.
Seminar: Presentation (30–45 minutes) with written paper (5–10 pages)
After agreeing on the specific task with the examiner, students present the significance and systematic scientific classification of a problem discussed in the seminar as part of their presentation and explain and present their topic in writing in their paper, incorporating aspects from the discussion in the seminar. The task may also include the development of an application (i.e. programming/calculation, etc.) of a procedure to a typically practically significant individual case. The presentation with written paper refers to the content taught in the seminar and developed in the exercises.
Lecture: Final exam (90-180 minutes) or final oral exam (20-40 minutes) on the content taught in the lecture and developed in the exercises.
The exam can alternatively be taken as an e-exam, open book exam or e-open book exam. In the case of open book exams and e-open book exams, the duration is 120-180 minutes.
Alternatively, an essay (approx. 4 pages) with a task strongly related to the knowledge and skills taught can be assigned. This is a reflective assignment on the systematics and interrelationships of the learning content or an examination of a programming task related to the content learned.
Both portfolio elements are assessed by an examiner. A final overall assessment is made.
Upon completion of module part 1 with the introductory lecture and accompanying seminar.
Portfolio with final examination consisting of:
1) Portfolio in the accompanying seminar: Presentation with elaboration
After agreeing on the specific task with the examiner, the students present the significance and systematic scientific classification of a problem discussed in the seminar/lecture as part of the presentation and explain and present their topic in writing in their elaboration, incorporating aspects from the discussion in the seminar. The task may also include the elaboration of an application (i.e. programming/calculation, etc.) of a procedure to a typically practically significant individual case.
2) A final examination on the introductory lecture:
The final examination on the contents of the lecture refers to the contents of the seminar or develops from the skills learned in the seminar.
Further details, in particular regarding the duration of the final examination, are provided in the course description.
In the final written examination/oral examination, students demonstrate their mastery of the exemplary application of abstractly learned skills beyond the specifically chosen topic of the presentation/paper.
Final written examination (90-180 minutes) or oral examination (20-40 minutes).
The written examination can alternatively be taken as an e-exam, open book exam or e-open book exam. In the case of open book exams and e-open book exams, the duration is 120-180 minutes.
Alternatively, an essay (approx. 4 pages in length) with a task strongly related to the knowledge and skills taught can be provided. This is a reflective task on the systematics and interrelationships of the learning content or an examination of a programming task related to the content learned.
Both portfolio elements are assessed by an examiner. A final overall assessment is then made.
Partial examination 2
When completing module partial examination 2 with the course ‘In-depth project’:
Project report (10-15 pages) including final presentation (20-30 minutes).
Upon completion of module part examination 2 with the course ‘Advanced Seminar’:
Presentation (20–30 or 30–45 minutes in length) with written paper (10–12 pages in length)
Upon completion of module part examination 2 with the course ‘Advanced Exercise’ or ‘Advanced Exercise (Alternative)’:
Portfolio of exercises and/or programming tasks that are set for each course.
The assessment of the exercises/programming tasks also includes direct questions about the solutions, which must be answered by the students in the exercises. Due to the equipment required, it may only be possible to work on the exercises in the exercise room. The course organiser may require individual explanations and demonstrations of tasks and may replace some of the exercises or programming tasks with classroom exercises. The tasks within the portfolio are usually assigned on a weekly basis.
Upon completion of module part 2 with the courses ‘Lecture on the second topic’ and ‘Exercise on the second topic’:
Portfolio with final examination consisting of:
1) Portfolio of exercises on the content of the lecture on the second topic
Exercise tasks or programming tasks that are set in relation to the course (pass mark 50% of the achievable points). The assessment of the exercise tasks also includes direct questions on the solution approaches, which must be answered by the students in the exercises. The lecturer may require individual explanations and demonstrations of tasks and may replace some of the exercises with classroom exercises. The exercises in the portfolio are usually assigned on a weekly basis and serve to accompany the independent implementation of the learning content presented in the seminar/lecture.
2) Final examination in the lecture on the second topic
The final examination on the contents of the lecture refers to the exercise or programming tasks or is based on the skills learned in the exercises.
Further details, in particular regarding the duration of the final examination, can be found in the course description.
Final written examination (90-180 minutes) or final oral examination (20-40 minutes) on the content taught in the lecture and covered in the exercises
The exam can alternatively be taken as an e-exam, open book exam or e-open book exam. In the case of open book exams and e-open book exams, the duration is 120-180 minutes.
Alternatively, an essay (approx. 4 pages) with a task strongly related to the knowledge and skills taught can be set. This is a reflective assignment on the systematics and interrelationships of the learning content or an examination of a programming task related to the content learned.
Both portfolio elements are assessed by an examiner. A final overall assessment is then made.
| Degree programme | Profile | Recommended start 3 | Duration | Mandatory option 4 |
|---|---|---|---|---|
| Data Science / Master of Science [FsB vom 01.04.2026, gültig ab WS 2026/2027] | Variante 1 | 1. o. 2. o. 3. | 2 semesters | Compulsory optional subject |
| Data Science / Master of Science [FsB vom 01.04.2026, gültig ab WS 2026/2027] | Variante 2 | 1. o. 2. o. 3. | 2 semesters | Compulsory optional subject |
The system can perform an automatic check for completeness for this module.