Technische Universität Ilmenau

Bachelor Seminar Data Science - Interactive curriculae of TU Ilmenau

The interactive curriculae provide information on the degree programmes offered by the TU Ilmenau.

Please refer to the respective study and examination rules and regulations for the legally binding curricula (Annex Curriculum).

You can find all details on planned lectures and classes in the course catalogue.

Please note that this page is no longer updated. All modules and study plans from PO version 2021 onwards (Bachelor and Master study programs) are now available on the Campus Portal.

module properties Bachelor Seminar Data Science in degree program Bachelor Data Science 2025
module number201353
examination number2400949
departmentDepartment of Mathematics and Natural Sciences
ID of group 24 (Fakultät für Mathematik und Naturwissenschaften)
module leader Manja Krümmer
term winter and summer term
languageEnglisch
credit points5
on-campus program (h)0
self-study (h)150
obligationobligatory module
examalternative pass-fail certificate
details of the certificate

The alternative coursework consists of
- seminar report (written work of appropriate length for the topic)
- 30 minutes presentation followed by discussion

link to Moodle course
teacher

Lecturers from the computer science disciplines of Faculty Computer Science and Automotion and from the Institute of Mathematics

signup details for alternative examinations
maximum number of participants
previous knowledge and experience
learning outcome

As part of a current problem with a defined task, students are able to familiarize themselves with a complex issue by studying the relevant literature. They can acquaint themselves with current scientific findings, analyze and evaluate them. They are able to summarize and contextualize insights from the literature and present them in a seminar report. They can present the information they have worked on in a presentation and reflect on it in a discussion.

content

The Data Science seminar teaches students how to work with scientific literature in the field of data science and effectively present their findings. Additionally, students will acquire the following skills:
• Developing a scientific or technical topic under supervision
• Documenting their work (including literature review and the current state of knowledge)
• Writing a structured seminar paper
• Presenting results in a professional manner, followed by a critical discussion

media of instruction and technical requirements for education and examination in case of online participation

Written documentation and lecture with digital presentation

literature / references

Topic-specific literature will be provided by the supervisor, and additional sources should be independently researched by the student.
It is also recommended to consult literature on academic writing, literature research (such as resources provided by the library), and presentation techniques.

evaluation of teaching