Data Science for Business Managers

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Data Science for Business Managers - Course Details

Delve into the course contents and find out about the faculty members.

This module will take place from Sept. 24-26 and Oct. 1-2, 2021. Course fee: €1,450 (+7% VAT). 

In order to book the course with alumni conditions, please get in touch with Manon Pfeifer directly.

Course Description

Contents:
“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.

Course Objectives:
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:

  1. Data Science for Managers
  2. Introduction in to Big-Data Management: Managing Data Quality and Improving Data Governance
  3. Data Monetization: Converting Data Into Financial Value
  4. Value Creation Through Data And Management Analytics – How Data Help To Transform The Company?
  5. A/B Testing And Experiments
  6. Linear Regression I
    • Understanding relationships
    • “Eye-Conometrics”: Graphics and economic relationships
    • Introduction to equation estimation
    • Making sense out of  residuals
    • From data to action
  7. Linear Regression II
    • Understanding complex relationships in the company
    • Observe what others cannot see
  8. Regression diagnostics
    • Using statistical tools to improve the company’s performance
    • Differences between useful and useless tools
  9. Predictive Analytics
    • Incorporate time to your models
    • Time series
    • Machine learning to account for time in your models

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:

  • Data Science With R
  • Data Science With Python

 

Lecturers

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Prof. Dr. Florian Stahl

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.

Publications:
Most recently in Journal of Research in Marketing, Journal of Marketing and International Journal of Research in Marketing
 

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Dr. José Parra-Moyano

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. 
 

MANNHEIM BUSINESS SCHOOL (MBS)

Located in the heart of the German and European economy, Mannheim Business School (MBS), the umbrella organization for management education at the University of Mannheim, is considered to be one of the leading institutions of its kind in Germany and is continuously ranked as Germany’s #1.

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