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The module Applied Predictive Analytics (APA) gives students an opportunity to work on a real-life predictive modeling project. The module is organized as a seminar. Seminar topics and specific (modeling) tasks will be announced shortly before the begin of the seminar. Typically, topics/tasks relate to business decision problems, for example in the scope of marketing or finance. The students will work collaboratively on a topics in groups with two to four members. Generally speaking, seminar work will include literature research, academic writing, empirical analysis, programming, and the presentation of research outcomes.
APA offers students the opportunity to develop a variety of skills, including:
- Students further develop their teamwork and project management abilities, and learn about contemporary software tools for collaborative work (GitHub, Trello, Slack,…).
- Students further advance their experience with contemporary software packages for data science and machine learning.
- Students are able to develop advanced forecasting models using a variety of algorithms from statistics, machine learning, and other domains.
- Students advance their knowledge in data integration, preparation, and transformation, which allows them to create predictive variables from noisy real-world data sets.
The organization of the seminar comprises several stages. After forming a group and receiving a topic/task, students will start with some background research and discuss their progress in weekly consultation sessions with their topic supervisor. The second stage will consist of weekly sessions with group presentations and discussions. Thereafter, the groups will have time to finalize their seminar paper, which will be the basis for performance assessment and grading in the seminar.
It is understood that successful completion of the module Business Analytics and Data Science is a mandatory prerequisite to participate in the seminar.
Max. number of participants: 24. If there are more than 24 applicants, seminar places will be allocated by draw.
Application: 1.02. - 10.04.2024 on AGNES |
