====== Seminar: Good Scientific Practice in Computer and Data Science ======

===== Key information =====

|| Contact || [[about:people:sascha_safenreider|Sascha Safenreider]], [[about:people:julian_kunkel|Julian Kunkel]], [[about:people:lorenz_glissmann|Lorenz Glissmann]] ||
|| Location || [[tba]] ||
|| Time || tba ||
|| Language || German ||
|| Module || 500132 Good Scientific Practice in Computer and Data Science ||
|| SWS || - ||
|| Credits || 2 ||

Participants develop an understanding of the basic principles of good scientific practice. They will be able to place scientific work in a broader context and understand the importance of integrity and responsibility in research. They deal intensively with aspects of quality assurance and learn to critically scrutinize scien-tific statements. They also acquire knowledge about ethical challenges in research and develop strategies to avoid conflicts and misconduct in the scientific environment.


===== Learning Objectives =====

After successfully completing the module, students will be able to...
  * effectively structure a research paper,
  * are familiar with formal and structural norms regarding outlines, formatting, bibliographies, etc.,
  * identify the principles of good scientific writing, apply them to their own writing and revise the manu-scripts of others accordingly,
  * participate in technical and scientific discussions,
  * give constructive feedback to colleagues,
  * present a research project they have worked on and lead a technical discussion about it.



===== Agenda =====

The agenda will be updated shortly.