Delve into the course contents and find out about the faculty members.
“Data Science for Business Managers” is designed to introduce participants to key concepts, tools, and practices of data science from a managerial perspective. The objective of the course is to provide the participants with the analytical tools that will help them to generate insights from data in a robust, correct, and actionable way. While the course has a solid theoretical foundation, it is designed to be a hands-on course in which the participants apply the learnings from the first day onwards, solving cases and problems. The course consists of two parts. In the first part of the course participants will learn and discuss various aspects of big data and data science from a business and managerial perspective, discuss the evolution of data-driven business models, managing data quality and data governance and improve their data literacy. The second part of the course starts with the basics of statistics and ends up introducing machine learning models to incorporate time components in predictive analytics. The software used in class to solve the cases is R.
In this course participants will have exposure to state-of-the-art methodologies for data science. The main objective of the course is that the participants learn how to gather, treat and clean data, as well as analyze it using different methods and generate insights that shall serve them to gain knowledge about their fields. The overall objective of this course is that participants feel comfortable and fluent when working with data, and that they learn how to use different methods to generate insights from the data. Moreover, the course teaches participants how to model functions and how to make simulations to generate further knowledge.
Course Composition and Teaching Methods:
The participants of this course will learn the foundation of data-driven management and business development as well as a profound introduction into data-science methods, and will apply them to real-world cases. This course covers a wide range of up-to-date data-science methods and their application.
The course is split into nine parts:
These concepts and tools will be introduced in class. Multi-Competence Teams (MCTs) formed by the participants will solve cases in which they will have the opportunity to apply the learned concepts. By doing this, they will acquire skills that will help them increase their performance in corporate and entrepreneurial environments.
Optional tutorials included:
Academic Director for the Mannheim Master in Management Analytics, Chair holder Quantitative Marketing and Consumer Analytics at the University of Mannheim
Researched / taught previously at:
Florian Stahl earned a Master's Degree in Economics from the University of Zürich (Switzerland) in 2001 and a PhD in Business Economics in 2005 from the University of St. Gallen (Switzerland). Between 2005 and 2008, he was a postdoctoral research fellow at Columbia Business School in New York. Before joining the University of Mannheim faculty of business administration in 2013, he was an Assistant and Associate professor (with tenure) of Quantitative Marketing at the Department of Business Administration of University of Zürich.
Fields of interests / research areas:
Florian Stahl's research interests are primarily in empirical quantitative marketing, business economics and information systems research. Specifically, his research addresses business related questions of the digital economy and, in particular, of online social networks and social media. Methodically his research is based on empirical modeling, applied econometrics, Bayesian modeling and experimental studies (laboratory as well as field experiments). The results of Florian Stahl's research have been published in top-tier journals such as Journal of Marketing or Journal of Marketing Research and won the 2012 H. Paul Root Award and the 2012 Robert D. Buzzell / Marketing Science Institute Best Paper Award.
Most recently in Journal of Research in Marketing, Journal of Marketing and International Journal of Research in Marketing
José Parra-Moyano is an Assistant Professor at the Copenhagen Business School, and holds a PhD in Management and Economics from the University of Zurich. He is an economist trained in statistical methods, and an expert in the application of technology in business administration, area in which he has several academic publications in FT50 and top-tier journals. His filed of research is the management and economics of privacy and data.
Besides that, José has been listed as FORBES 30 UNDER 30, has been appointed as Global Shaper by the World Economic Forum, and is a Research Fellow at the Blockchain Centre of the University College in London. Moreover, he sits in the board of different companies, advising them in the development of their strategies and in the integration of technology into their core business.
José gives courses about blockchain, statistics, and business analytics in different universities at master and MBA level.