Software Development 1

Master's degree program

The participants:

• can apply the basic concepts of software development (e.g., object orientation, functional programming, etc.) that are frequently used in the field of data science
• can apply the concepts they have studied in software development environments commonly used in data analysis (e.g., in Python)
• can identify the common tools used in software development within data science
• can design basic applications in order to automate basic functionalities
• can independently implement the applications they have designed

Students have prior knowledge in information technology equivalent to 6 ECTS and are therefore familiar with basic programming concepts (e.g., variables, branching, loops) as well as typical programming approaches (e.g., functional programming).

The following topics are covered in the course:

- The process of software engineering and project management for data-intensive applications
- Programming paradigms for use in the field of data science
- Effective and efficient data structures for data-intensive applications
- Tools and software ecosystems for the development and testing of data-intensive software systems

- Lutz, M (2025): Learning Python, O'Reilly (ISBN: 978-1098171308)
- 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 Kaufmann, Burlington (ISBN: 978-0128042069)

Written exam

English

6

The following methods are used:

- Lecture with discussion
- Working on practice exercises
- Interactive workshop

1