WIW34200 – Applied Programming Project

Modul
Applied Programming Project
Applied Programming Project
Modulnummer
WIW34200
Version: 1
Fakultät
Wirtschaftswissenschaften
Niveau
Master
Dauer
1 Semester
Turnus
Wintersemester
Modulverantwortliche/-r

Prof. Dr. Christian Brauweiler
Christian.Brauweiler(at)fh-zwickau.de

Dozent/-in(nen)

Lecturer of the Armenian State University of Economics (ASUE)

Dozent/-in in: "Applied Programming Project"

Lecturer of the International Black Sea University (IBSU)

Dozent/-in in: "Applied Programming Project"

N.N.

Dozent/-in in: "Applied Programming Project"

Lehrsprache(n)

Englisch
in "Applied Programming Project"

ECTS-Credits

5.00 Credits

Workload

150 Stunden

Lehrveranstaltungen

2.00 SWS (2.00 SWS Vorlesung mit integr. Übung / seminaristische Vorlesung)

Selbststudienzeit

120.00 Stunden
80.00 Stunden Projekt(e) - Applied Programming Project
40.00 Stunden Selbststudium - Applied Programming Project

Prüfungsvorleistung(en)
Keine
Prüfungsleistung(en)

alternative Prüfungsleistung - Softwareprojekt
Modulprüfung | Wichtung: 100% | wird in englischer Sprache abgenommen
in "Applied Programming Project"

Medienform
Keine Angabe
Lehrinhalte/Gliederung

Programming project:

  • Build a team for conducting the programming project
  • Selection of topics
  • Planning of the project
  • Programming of the project
  • Reporting and presentation of the results
Qualifikationsziele

Students shall work together in interdisciplinary groups and plan, structure and conduct a software project solving practice-oriented real-world problems. In addition, students can apply system programming languages and manage a software project. Furthermore, they can apply their existing in-depth knowledge to their projects and develop their software applications. Moreover, they need to master the goal-oriented implementation of known methods of project management (goal definition, resource planning, personnel management, time planning, interface planning, communication, conflict resolution, protocol management, presentation of interim results, planning control, planning update, progress monitoring, project meetings, system analysis, evaluation, development, configuration management, change management, tests).

The core of this subject is an individual practice-oriented programming project. Students will form an interdisciplinary team to apply their programming knowledge and solve a practice-oriented programming task. Since the study program is also offered to non-computer scientists, students with high-level programming skills shall work with lower-level students. As a team, they will cover different software project tasks, think of creative solutions, apply their programming skills, and learn from each other through the guidance of the lecturer. They will report on each step and present their solution at the end of this subject.  

Social and Personal Skills:

The students will train their communication skills through group work and presentation preparation in the framework of the programming project. Furthermore, the students will improve their self-awareness and self-confidence by managing the projects independently. This will also improve their creativity as they work together in interdisciplinary teams with different professional backgrounds and expertise. Moreover, the students will deepen their knowledge of how to manage software projects.

Besondere Zulassungsvoraussetzung

keine

Empfohlene Voraussetzungen

Basic Programming Skills in Python or Java

Fortsetzungsmöglichkeiten
keine Angabe
Literatur
  • William B. Claster: Mathematics and programming for machine learning with R: from the ground up (CRC Press, 2020)
  • Wes McKinney: Python for Data Analysis (2. ed., O‘REILLY, 2017)
  • David Taieb: Data Analysis with Python (Packt Publishing, 2018)
  • Michal Jaworski, Tarek Ziadé: Expert Python Programming (4th ed., 2021)
Hinweise

For students who want to deepen their applied programming skills can choose the elective subject PTI90190 Computer Science Project. 

This subject connects to the later compulsory subjects PTI90290 Machine Learning, WIW64031 Analytics for Data Driven Decisions and PTI90310 Design and Implementation of Software Systems.