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CS 694 — Project Work Data Science
(dt. Projektarbeit Data Science)

Level, degree of commitment Practical module, required module
Forms of teaching and learning,
workload		 Independent familiarization and execution of the assigned task,
360 hours (360 h private study)
Credit points,
formal requirements		 12 CP
Course requirement(s):
Examination type: Software development (the term software includes all created artifacts, in particular, program code, planning documents, user and developer manuals, and presentation materials)
Language,
Grading		 English or German,
The module is ungraded in accordance with the examination regulations for the degree program M.Sc. Data Science.
Duration,
frequency		 Two semesters,
each semester
Person in charge of the module's outline All lecturers of Computer Science and Mathematics

Contents

Knowledge, methods and techniques from sub-areas of computer science are applied to a concrete problem. Procedure:

  • Familiarisation with and study of the literature relevant to the project
  • Project definition, planning and presentation of the project and its parts in the form of seminar presentations after the induction phase.
  • Structuring of the project into partial problems, scheduling of the processing of partial problems and the integration of partial solutions, definition of subgroups for the processing of partial tasks, definition of interfaces, etc.
  • Documentation and operating instructions for software systems
  • Monitoring the progress of the work and adherence to the schedule.
  • Preparation of a final report containing a systematic description of the problem dealt with and the solution adopted, a description of the factual and temporal structuring of the problem handling and the compilation and discussion of the results obtained.
  • Presentation of the completed project in a public lecture

Qualification Goals

The students

  • are able to work on an extensive task from computer science / data science in a team of several students. This includes: working out, adapting, extending and developing problem-relevant methods
  • can plan and carry out the modeling and processing of data within the framework of a project,
  • are able to learn, plan and work independently,
  • are proficient in project management and monitoring methods, e.g.: goal descriptions, planning, milestones, record keeping, deadlines, delegation, controlling;
  • have team-related social skills: Collaboration, team development, leadership, motivation, well-structured staff team, working under deadline pressure,
  • are proficient in methods of documenting and presenting information technology projects to users and third parties in the form of program documentation, project reports, and publications as appropriate.

Prerequisites

None.


Applicability

The module can be attended at FB12 in study program(s)

  • M.Sc. Data Science

When studying M.Sc. Data Science, this module must be completed in the study area Practical and Seminar Modules.


Recommended Reading

  • Depending on the development task



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2023/24. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.