BWL XI: Courses in Winter Semester 20/21
In winter semester 20/21, we offer the course "Text Mining" for master's students. Bachelor's students are welcome to apply for a spot in the "Data Science Proseminar." Proseminar participants are welcome to propose seminar topics based on their personal interests.
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 20 / 21
- Language: English
- Grading: Presentation & Term Paper
- Schedule: See course flyer
The number of participants is limited to a maximum number of 24 students. Please register for the course by sending an e-mail to Prof. Dr. Nicolas Pröllochs (nicolas.proellochs@wi.jlug.de). Please attach your current transcript of records (FlexNow printout). If more than 24 students apply, participants will be selected based on their grade in the course "Data Science for Management" and/or their current GPA. The application deadline is October 15, 2020 (early applications are encouraged). The course is also opened to interested bachelor students currently enrolled in the 210- and 240-CP programs.
Proseminar (B. Sc.) in Data Science
Data science is the field of study that combines domain expertise, programming skills, and knowledge of maths and statistics to extract meaningful insights from data. In this seminar, we will focus on Data Science methods and tools. Examples include machine learning models, data visualization, model selection, clustering, and forecasting. We will also review best practices in scientific writing. Students are welcome to propose seminar topics based on their personal interests. Basic experience in R programming is desirable but not mandatory. Please indicate your level of programming expertise. Individual assignments will consist of a specific problem from data science. Grading will be based on a seminar paper and an oral presentation.
Exemplary topics include, but are not limited to:
- Applying a data science method to a dataset (e.g. predicting movie ratings based on movie reviews)
- Presenting an R package
- Presenting a data science / machine learning method
Organization:
- Lecturer: Prof. Dr. Nicolas Pröllochs (BWL XI)
- Course format: Semianr
- Term: winter semester 20/21
- Language: German
- Grading: Seminar paper & presentation