Syllabus
Introduction to Programming [INF40043]
| Field | Details |
|---|---|
| Instructor | Wagner, Gerit |
| Module Coordinator | Roßbach, Peter |
| Programme(s) | Bachelor of Science |
| Term | Semester 1 |
| Module Duration | 1 Semester |
| Compulsory/Elective Module | Compulsory Module |
| Credits | 6 |
| Frequency | Annually |
| Language | German |
| Total Workload | 150 h |
| Academic Teaching Hours | 44 |
| Remaining Workload | Self-study |
| Prerequisites | None |
One academic teaching hour corresponds to 45 minutes.
Self-study includes lesson preparation and follow-up activities, reading assignments, preparation for tests and examinations, take-home assignments, etc.
Content
The course introduces students to two core tools for solving business and numerical problems:
- Introduction to Excel
- Introduction to Python
The first part of the module focuses on developing applications with Excel. Starting from Excel, students learn the principles of spreadsheet applications and their use in a business context.
The second part introduces the Python programming language. Python is used as a tool for exercises in subsequent courses such as Stochastics and Applied Research Methods.
Practical exercises are conducted throughout the course, both in class and at home.
Intended Learning Outcomes
Knowledge
After completing the course, students are familiar with the fundamental concepts of Excel and the Python programming language. They can:
- Explain how computer programs work.
- Describe the fundamental principles of spreadsheet applications.
- Explain different data types and control structures in Python.
- Demonstrate the use of an integrated development environment.
Skills
After successfully completing the course, students are able to apply their knowledge. They can:
- Create Excel applications according to specific business requirements.
- Develop simple computer programs in Python.
- Perform data analysis using both Excel and Python.
- Find and fix errors in code.
Competences
After successfully completing the course, students are able to:
- Translate business and numerical problems into Excel or Python solutions.
- Select appropriate data structures.
- Develop corresponding code.
- Implement solutions with a focus on quality.
Forms of Teaching, Methods, and Support
Interactive lectures with case studies and exercises.
Assessment
| Type of examination | Duration or length | Performance Points | Due date or date of exam |
|---|---|---|---|
| Excel | 40 minutes | 40 | Mid-term examination week |
| Python | 80 minutes | 80 | Examination week |
Recommended Literature
TBA.
Module Structure
The module consists of two parts.
1. Excel
The first part takes place in the first quarter and focuses on developing applications with Excel. Starting from Excel, students learn the principles of spreadsheet applications and their use in a business context.
2. Python
The second part takes place in the second quarter and introduces the Python programming language. Python is used as a tool for exercises in subsequent courses such as Stochastics and Applied Research Methods.
Practical exercises are conducted throughout the course. The exercises are completed both in class and at home.
Relevance for Other Modules and Programmes
- Advanced Business Modeling Using Spreadsheets
- Stochastics
- Applied Research Methods