| Detailinformationen |
| Anmeldevoraussetzungen |
(*)Kenntnisse über Windows/Mac/Linux und Anwendungsprogramme sowie die Organisation von Ordnern und Dateien werden erwartet.
Knowledge of Windows/Mac/Linux and application programs, as well as the organization of folders and files is expected.
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| Quellcurriculum |
Masterstudium Economic and Business Analytics 2025W |
| Lernergebnisse |
Kompetenzen |
(*)- Python basics: Students will understand the syntax and structure of the Python programming language, including variables, data types, and control structures.
- Problem-Solving: Students will develop problem-solving skills by working on assignments and projects, applying Python programming concepts to real-world scenarios.
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| Fertigkeiten |
Kenntnisse |
(*)- Learning Outcome 3 (LO3): Students will apply their knowledge, and understanding of Python syntax
- Learning Outcome 4 (LO4): Students will evaluate appropriate data structures and data types for various problem-solving scenarios
- Learning Outcome 5 (LO5): Students will identify libraries commonly used in data analytics.
- Learning Outcome 6 (LO6): Students will solve simple programming problems, incorporating control structures, data types, and algorithms covered in this course.
- Learning Outcome 7 (LO7): Students will distinguish between object-oriented programming and functional programming.
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(*)- Learning Outcome 1 (LO1): Students will understand the basics of setting up a Python programming environment.
- Learning Outcome 2 (LO2): Students will comprehend and apply the basics of Python programming, such as variables, data types, and control structures.
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| Beurteilungskriterien |
(*)The VL and UE Python Programming for Economic and Business Analytics will be graded in conjunction. The total score for the course is 100 points, with 50 points (50%) allocated to the final exam and the remaining 50 points (50%) to homework exercises. A minimum of 50 points is required to pass the course. The following table details how the final grades are assigned based on the total points earned
| Points | Grade |
|---|
| 87,5 - 100 | 1 |
| 75 - 87 | 2 |
| 62,5 - 74,5 | 3 |
| 50 - 62 | 4 |
| 0 - 49,5 | 5 |
- Exam: The exam is conducted individually, with an option for a retry exam in case of unsatisfactory results or scheduling conflicts.
- The exam includes both theoretical and practical questions involving the implementation of solution algorithms.
- It has a duration of 180 minutes
- Exercises:
- There are five homework assignments (each worth 8 points) that must be submitted via Moodle. Feedback will also be provided through Moodle.
- An additional 10 points can be earned for presenting the solutions to a previous assignment orally
- The total possible points for exercises is calculated as 5 x 8 + 10 = 50 points.
Synchronisation of learning outcomes and assessments:
- LO1: Final Exam + Exercises
- LO2: Final Exam + Exercises
- LO3: Final Exam + Exercises
- LO4: Final Exam + Exercises
- LO5: Final Exam + Exercises
- LO6: Final Exam + Exercises
- LO7: Final Exam + Exercises
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| Lehrmethoden |
(*)The primary teaching method involve lectures supported by slides and practical examples to provide foundational concepts, which students will apply in corresponding exercise modules. The integration of lecture slides and exercises is designed to effectively communicate the stated learning outcomes to students.
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| Abhaltungssprache |
Englisch |
| Literatur |
(*) |
| Lehrinhalte wechselnd? |
Nein |
| Sonstige Informationen |
(*)Attendance is mandatory.
Introduction to Software Development in Python consists on the practical exercises and the theoretical part. They are assessed together.
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| Frühere Varianten |
Decken ebenfalls die Anforderungen des Curriculums ab (von - bis)
977PADTPYTV21: VL Python Programming for Economic and Business Analytics (2021W-2022S)
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