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Software development 2 Lab
level of course unit
Master's courseLearning outcomes of course unit
The following skills are developed in the course:
- Students can implement advanced application concepts independently.
- Students can develop advanced application concepts and bring them into an implementable form.
- Students can implement advanced application concepts independently.
- Students can develop advanced application concepts and bring them into an implementable form.
prerequisites and co-requisites
1st semester: Students will have previous knowledge in the field of information technologies to the extent of 6 ECTS and therefore know the concept of the relational database and can read simple SQL queries. / 1st semester: Students will have previous knowledge in the field of information technologies to the extent of 6 ECTS and therefore know simple programming concepts (e.g. variables, branches, loops) as well as typical programming approaches (e.g. functional programming). / 2nd semester: SDDE.A1 module examination (Software Development 1)
course contents
In the lab, the contents of the ILV “Software Development 2” are advanced with the aid of practical exercises. The knowledge gained will be discussed in the group and thus allow a deep insight into the material and consolidation of the knowledge, which was theoretically dealt with in the ILV.
recommended or required reading
PRIMARY LITERATURE:
- Lutz, M (2013): Learning Python (Ed. 1), O'Reilly Media, Farnham (ISBN: 978-1449355739)
SECONDARY LITERATURE:
- Sommerville, I. (2015): Software Engineering, Global Edition (Ed. 10), Pearson Education, London (ISBN: 978-1292096131)
- Williams, L.; Zimmermann, T. (2016): Perspectives on Data Science for Software Engineering (Ed. 1), Morgan Kauf-mann, Burlington (ISBN: 978-0128042069)
- Crawley, M. J. (2007): The R Book (Ed. 1), John Wiley and Sons Ltd, Chichester (ISBN: 978-0-470-51024-7)
- Lutz, M (2013): Learning Python (Ed. 1), O'Reilly Media, Farnham (ISBN: 978-1449355739)
SECONDARY LITERATURE:
- Sommerville, I. (2015): Software Engineering, Global Edition (Ed. 10), Pearson Education, London (ISBN: 978-1292096131)
- Williams, L.; Zimmermann, T. (2016): Perspectives on Data Science for Software Engineering (Ed. 1), Morgan Kauf-mann, Burlington (ISBN: 978-0128042069)
- Crawley, M. J. (2007): The R Book (Ed. 1), John Wiley and Sons Ltd, Chichester (ISBN: 978-0-470-51024-7)
assessment methods and criteria
The following examination methods are used in the course:
- Project work
- term paper
- Project work
- term paper
language of instruction
Germannumber of ECTS credits allocated
2.5eLearning quota in percent
0course-hours-per-week (chw)
1planned learning activities and teaching methods
The following methods are used:
- Processing of exercises
- Interactive workshop
Data Engineering /ILV / Course no.: SDDE.1 / 1st semester / ECTS: 4
- Processing of exercises
- Interactive workshop
Data Engineering /ILV / Course no.: SDDE.1 / 1st semester / ECTS: 4
