Advanced Business Analytics
Content and goals of the course
The problems faced by decision makers in today’s competitive business environment are complex and multi-faceted, and often require skills that go beyond theoretical data science knowledge. Solving such problems effectively requires the employment of a structured approach to business problem-solving.
Advanced Analytics is defined by Gartner as “the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations.”
Advanced Analytics refers to the fields of Machine Learning, Predictive Analytics, Process Mining, Text Mining, and Social Network Analysis, to name a few. It is presumed that participants are familiar with the theoretical concepts from one or more of the mentioned data science areas. The focus of the seminar is on the application of those concepts on given use cases from industry.
Students gain practical skills in extracting and manipulating structured and unstructured data, executing methods for descriptive, predictive, or prescriptive analysis, and effectively interpreting and presenting analytic results. Thus, students do not only get hands-on technical experience but also gain domain knowledge and learn soft-skills relevant for data scientist (e.g., teamwork, critical thinking, storytelling).
This course is mostly organized as a self-study. Work will be done in groups of three to five students.
All topics are presented and explained in the Kick-off, as well as organizational issues and other relevant information.
Teams will have to present their progress on the chosen topic.
Course registration for the winter term 22/23
Registration is required. Places are limited. The seminar is open only for students from the Master in Data Science Program.
Registration is done via StudOn until 07.10.2022.
Kick-off: 20.10.2022 at 11 AM via Zoom
|Advanced Business Analytics Seminar (59851)
100% of the grade is based on the final presentation.