course: Master Project DSP

number:
142040
teaching methods:
project
media:
overhead transparencies
responsible person:
Prof. Dr.-Ing. Do­ro­thea Kolossa
Lecturers:
Prof. Dr.-Ing. Do­ro­thea Kolossa (ETIT), Dr.-Ing. Steffen Zeiler (ETIT)
language:
german
HWS:
3
CP:
see examination rules
offered in:
summer term

dates in summer term

  • start: siehe "Sonstiges"

Exam

All statements pertaining to examination modalities (for the summer/winter term of 2020) are given with reservations. Changes due to new requirements from the university will be announced as soon as possible.
Form of exam:project
Registration for exam:None
continual assessment

goals

In addition to strategies and methods for the solution of technical challenges, the students learn the organization of large projects in teams, methods of project planning, and structured software development including specification and unit testing.

content

During the course of the semester, students develop a larger DSP project in teams of 2 to 10 students. The project is usually implemented in real time on a current DSP platform.

In the summer semester 2020, no physical participation is possible. We want to, instead, use this format to allow students to participate in one of the COVID-19 Challenges at Kaggle, cf. https://www.kaggle.com/covid19

Before the start of the project lab, interested students should team up in a group of 2-10 members (as a possible support, you'll find a discussion forum in the course Moodle), should familiarize themselves with the tasks posted at Kaggle, select the challenge they plan to address, and register for the lab via email. Registration ends on April 23.

In the course of the semester, the lab is supported in the form of a weekly online meeting, in which participation is mandatory. To pass the lab, we expect a submission of the best-performing solution to kaggle, a final report which documents the code and its performance, and a final presentation via an online meeting tool.

requirements

keine

recommended knowledge

  • Basic knowledge of digital signal processing and machine learning
  • good programming skills
  • ideally, experience in Python programming

miscellaneous

Im Som­mer­se­mes­ter 2020 ist keine An­we­sen­heit mög­lich. Wir möch­ten es aber Stu­die­ren­den er­mög­li­chen, sich in die­sem Rah­men an den CO­VID-19 Chal­len­ges bei Kagg­le zu be­tei­li­gen, siehe https://​www.​kaggle.​com/​covid19

Link zum Moodle-Kurs: https://moodle.ruhr-uni-bochum.de/m/enrol/index.php?id=26991