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Foto: Universität Paderborn, Jörg Ullmann Show image information
Foto: Universität Paderborn, Jörg Ullmann Show image information
Foto: Universität Paderborn, Jörg Ullmann Show image information

Foto: Universität Paderborn, Jörg Ullmann

Foto: Universität Paderborn, Jörg Ullmann

Foto: Universität Paderborn, Jörg Ullmann

Teaching

Python-Crashkurs

Im Wintersemester 2019/20 bietet unser Fachgebiet in Kooperation mit dem Fachgebiet Elektrische Messtechnik (https://ei.uni-paderborn.de/emt/lehre/lehrveranstaltungen/ws-20192020/python-crashkurs/) einen Python-Crashkurs im Umfang von 3 x 2h an. Ziel dieses Crashkurses ist es, Studierenden eine Einstiegshilfe zu geben, um Python-Grundlagen zu lernen, welche in mehreren unserer Veranstaltungen (VSS, SML, OAF, ...) aber auch in den Veranstaltungen anderer Fachgebiete genutzt werden können.  

Der Crashkurs besteht aus drei Blöcken zu jeweils 2 Stunden:

  • Einrichtung von Python (Notebook oder Poolraum-Computer), Python-Grundlagen und Jupyter
  • Numerisches Python (numpy, scipy, ...)
  • Auswertung und Visualisierung (pandas, matplotlib, ...)

Der Kurs findet am 11.10.2019 und den beiden nachfolgenden Freitagen jeweils von 09:00 bis 11:00 im Poolraum P7.2.02.1 statt. Ein zweiter möglicher Termin kann je nach Nachfrage eingerichtet werden. Um die Teilnehmerzahl abschätzen zu können, melden Sie sich bitte für den Kurs in der jeweils ersten Stunde der Lehrveranstaltung VSS oder KSS an.

Die Teilnahme am Kurs ist optional und wird nicht bewertet. In den Programmierübungen zu den Veranstaltungen (VSS, SML, OAF, ...) wird jedoch auf die Vermittlung von Programmierkenntnissen nicht mehr weiter eingegangen.

Number Lecture Credits Instructor WS SS
L.048.10901 Communications Engineering L2/E2
ECTS 5
Häb-Umbach
Ebbers
 
L.048.23018
L.048.92030
Topics in Pattern Recognition and Machine Learning L2/E2
ECTS 6
Häb-Umbach
Böddeker
 
L.048.24010
L.048.92011
Optimal and Adaptive Filter L2/E2
ECTS 6
Schmalenströer
Gburrek
 
L.048.21004 Statistical Signal Processing L2/E2
ECTS 6
Häb-Umbach
Glarner
Heitkämper
 
L.048.10502 Project 'Applied Programming' E2 Ullmann  
L.048.10902 Elements of Digital Communication Systems L2/E2
ECTS 6
Häb-Umbach  
L.048.10908 Discrete-Time Signal Processing L2/E2
ECTS 6
Schmalenströer  
L.048.92005 Statistical and Machine Learning L2/E2
ECTS 6
Häb-Umbach  
L.048.24001 Digital Speech Signal Processing L2/E2
ECTS 6
Schmalenströer  
L.048.62003 Research Seminar 'Communications Engineering' S2
ECTS 3
Häb-Umbach
Schmalenströer
L.048.10809 Project Seminar Communications Engineering S2
ECTS 3
Häb-Umbach
L.048.98005 Communications Engineering  (Project) P6
ECTS 9
Häb-Umbach
Schmalenströer
L.048.98501 Communications and Speech Processing (Project) P6
ECTS 9
Häb-Umbach
Schmalenströer
L.048.98006 Digital Signal Processing (Project) P6
ECTS 9
Häb-Umbach
Schmalenströer

Degree program overview

Bachelor Studies Electrical Engineering (EBA)

1. Study Section Electrical Engineering Studies

  • L.048.10809 Project Seminar Communications Engineering

2. Study Section Electrical Engineering Studies

  • L.048.10901 Communications Engineering

2. Study Section Electrical Engineering Studies: Information Technology

  • L.048.10902 Elements of Digital Communication Systems
  • L.048.10908 Discrete-Time Signal Processing

2. Study Section with Minor Subject Vocational Education

  • L.048.10901 Communications Engineering
  • L.048.10809 Project Seminar Communications Engineering
  • L.048.10902 Elements of Digital Communication Systems
  • L.048.10908 Discrete-Time Signal Processing
Master Studies Electrical Engineering (EMA)

Compulsory Subject

  • L.048.21004 Statistical Signal Processing

Cognitive Systems

  • L.048.23018 Topics in Pattern Recognition and Machine Learning
  • L.048.23012 Statistical and Machine Learning

Communications

  • L.048.24010 Optimal and Adaptive Filters
  • L.048.24001 Digital Speech Signal Processing
  • L.048.24011 Video Technology
  • L.048.24004 Wireless Communications

Projects

  • L.048.28006 Digital Signal Processing (Project)
  • L.048.28005 Communications Engineering (Project)
Bachelor Studies Computer Engineering (CEBA)

2. Study Section: Compulsory Area

  • L.048.10901 Communications Engineering

2. Study Section: Mandatory Elective Module Electrical Engineering

  • L.048.10908 Discrete-Time Signal Processing
  • L.048.10902 Elements of Digital Communication Systems
Master Studies Computer Engineering (CEMA)

Compulsory Area

  • L.048.21004 Statistical Signal Processing

Area of Specialisation: Communications and Networks

  • L.048.24010 Optimal and Adaptive Filter
  • L.048.24004 Wireless Communications

Area of Specialisation: Signal, Image and Speech Processing

  • L.048.92030 Topics in Pattern Recognition and Machine Learning
  • L.048.24010 Optimal und Adaptive Filter
  • L.048.24011 Video Technology
  • L.048.23012 Statistical and Machine Learning
  • L.048.24001 Digital Speech Signal Processing
  • L.048.24004 Wireless Communications

Project Group Computer Engineering

  • L.048.28501 Project Group Communications and Speech Processing
Bachelor Studies Business Administration and Engineering (Electrical Engineering) (WGBAET)

Advanced Studies, Compulsory Elective Modules Engineering

  • L.048.10902 Elements of Digital Communication Systems
  • L.048.10908 Discrete-Time Signal Processing
  • L.048.10901 Communications Engineering

Advanced Studies, Project Seminars

  • L.048.62003 Research Seminar Nachrichtentechnik
Master Studies Business Administration and Engineering (Electrical Engineering) (WGMAET)

Compulsory Elective Modules Engineering

  • L.048.24011 Video Technology
  • L.048.24001 Digital Speech Signal Processing
  • L.048.24004 Wireless Communications
  • L.048.23012 Statistical and Machine Learning
  • L.048.23018 Topics in Pattern Recognition and Machine Learning
  • L.048.21004 Statistical Signal Processing
  • L.048.24010 Optimal and Adaptive Filters
Teacher Education for Vocational College Teachers for Electrical Engineering

Bachelor Studies

  • L.048.10502 Project Applied Programming

Master Studies: Subject-specific Studies

  • L.048.10901 Communications Engineering
  • L.048.10902 Elements of Digital Communication Systems

Master Studies: Minor Professional Discipline Automation Technology

  • L.048.10908 Discrete-Time Signal Processing
  • L.048.10902 Elements of Digital Communication Systems
  • L.048.23012 Statistical Learning and Pattern Recognition

Master Studies: Minor Professional Discipline Information Technology

  • L.048.24010 Optimal and Adaptive Filters
  • L.048.24004 Wireless Communications
  • L.048.10902 Elements of Digital Communication Systems
  • L.048.24001 Digital Speech Signal Processing
  • L.048.10908 Discrete-Time Signal Processing
  • L.048.24011 Video Technology
Master Studies Electrical Systems Engineering

Compulsory objectives: Module: Signal & Information Processing

  • L.048.92005 Statistical and Machine Learning

Compulsory electives: Module: Fundamentals of ESE

  • L.048.92041 Digital Speech Signal Processing

Compulsory electives: Module: Signal & Information Processing

  • L.048.92011 Optimal and Adaptive Filters
  • L.048.92030 Topics in Pattern Recognition and Machine Learning
  • L.048.92035 Wireless Communications

Compulsory electives: Module: ESE-Electives

  • L.048.92011 Optimal and Adaptive Filters
  • L.048.92030 Topics in Pattern Recognition and Machine Learning
  • L.048.92005 Statistical and Machine Learning
  • L.048.92035 Wireless Communications

Compulsory electives: Projects

  • L.048.28005 Communications Engineering (Project)
  • L.048.28006 Digital Signal Processing (Project)
Bachelor Studies WS 19/20

Communications Engineering

  • Lecture: Tue 9:00 - 11:00 (P7.2.03)
  • Exercise: Thu 11:00 - 13:00 (P7.2.03)
Master Studies WS 19/20

Topics in Pattern Recognition and Maschine Learning

  • Lecture: Thu 14:00 - 15:30 (P7.4.02)
  • Exercise: Thu 15:45 - 17:15 (P7.4.02)

Optimale and Adaptive Filter

  • Lecture: Mon 7:30 - 9:00 (P7.4.02)
  • Exercise: Mon 9:15 - 10:45 (P7.4.02)

Statistical Signal Processing

  • Lecture: Tue 14:00 - 15:30 (P7.2.03)
  • Exercise: Tue 16:00 - 18:00 (P7.2.02.1)
  • Exercise: Tue 16:00 - 18:00 (P1.6.12.4)
Ansprechpartner & Fragen
  • Bei Fragen zu Projekten, Vorlesungen und Übungen wenden Sie sich bitte an die angegebenen Dozenten.

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