BWL XI: Courses in Winter Semester 25/26
In winter semester 25/26, we offer the courses "Text Mining" and "Applied AI" for master's students. The number of participants is limited to a maximum number of 24 students. The deadline for applications is October 2, 2025.
Course: Text Mining (M. Sc.)
The digital age has ignited a burst in the volume of textual materials available to businesses and the public. Text mining provides computational techniques to derive actionable (managerial) insights from such unstructured data sources. The course “Text Mining” provides students with an overview of a wide range of text mining methods: from regular expressions to lexicon-based sentiment analysis, to more complex machine learning approaches and supervised text classification. At the end of the course, participants will be familiar with the most important concepts, principles, and algorithms in text mining. The course includes practical sessions focusing on text mining in R. Basic experience in R programming is desirable but not mandatory.
The main objectives of this course are:
- Understand the basic concepts of text mining and its relevance for business applications
- Gain an overview of different methods, algorithms and software tools for extracting knowledge from unstructured text data
- Practice the implementation of text mining applications in R
Organization:
- Module codes: 02-BWL/VWL:MSc-B11-1
- Lecturer: Prof. Dr. Nicolas Pröllochs (BWL XI)
- Course format: Lecture (6 CP)
- Term: Winter semester 25 / 26
- Language: English
- Grading: Presentation & Term Paper
- Schedule: See course flyer
Course evaluation by students (average 2019 – 2023): 1.4
The number of participants is limited to a maximum number of 24 students. Please register for the course by sending an e-mail to datascience@wirtschaft.uni-giessen.de (see course flyer). The application deadline is October 2, 2025 (early applications are encouraged). The course is also opened to interested bachelor students currently enrolled in the 210- and 240-CP programs.
Course: Applied AI (M. Sc.)
Artificial Intelligence (AI) is transforming the businesses by unlocking new opportunities for efficiency and data-driven decision-making. The master’s course on “Applied AI” provides students with an overview of the field of AI with a focus on real-world applications. Students will learn the end-to-end process of preparing data, implementing machine learning models, and evaluating their performance. The course will provide hands-on coding examples, equipping students with the necessary skills to implement these techniques independently. At the end of the course, participants will be familiar with the most important concepts, principles, algorithms, and challenges in applied AI.
The main objectives of this course are to:
- Understand the basic concepts of AI and machine learning and their relevance in business contexts
- Obtain an overview of different methods, algorithms, and software tools for applied AI
- Learn how to train and evaluate AI methods on real-world datasets
- Understand limits and challenges associated with contemporary AI methods, including ethical considerations and biases
Organisation:
- Module codes: 02-BWL/VWL:MSc-B11-Extra2
- Lecturer: Prof. Dr. Nicolas Pröllochs (BWL XI)
- Course format: Lecture (6 CP)
- Term: Winter semester 25/26
- Language: English
- Grading: Presentation
- Schedule: See course flyer
The number of participants is limited. The application deadline is October 2, 2025. Details about the application process can be found in the course flyer.