DS400 Data Science Project Management
Lecturer: | Prof. Dr. Stefan Mayer |
Course description: | DS400 |
Language: | English |
Recommended for this semester or higher: | 1 |
ECTS-Credits: | 9 |
Course can be taken as part of following programs/modules: | Data Science in Business and Economics |
Prerequisite for: | DS404B Big Data Computing |
Prerequisites: | Previous knowledge in programming is required (either R or Python), as well as basic knowledge in statistics. |
Course Type: | Lecture (4 weekly lecture hours) |
Date: | Beginning of the first session: Tuesday, October 18, 2022 from 2pm c.t. - 6pm (room PC Lab 008, ground floor, Nauklerstr. 47) |
Registration: | Limited to 28 participants. |
Downloads: | ILIAS |
Method of Assessment: | Written exam (90 Minutes), or oral examination, or assignments or presentation or online assessment (90 Minutes) |
Content: | The course deals with the workflow of empirical analyses, applying all steps from data collection through data management to data output. The focus is on dealing with large data sets and implementation of all data preparation and analysis steps in code to ensure replicability. The course will be taught “bilingual”: all procedures and analyses are explained both in R and Python, and students should be proficient in both languages by the end of the course. |
Objectives: | Through the tutorial, students will be able to reflect on the concepts presented in theory, and to apply these concepts to advanced research problems. |
Literature: | Grolemund, G. & Wickham, H. (2017): R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media. VanderPlas, J. (2016). Python Data Science Handbook. O’Reilly Media. jakevdp.github.io/PythonDataScienceHandbook/ |