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Courses on Service Research

Service Analytics

Prof. Setzer, Prof. Fromm, 4.5 Credits


Service Analytics II – Enterprise Data Reduction and Prediction

Prof. Setzer, 4.5 Credits


Services Marketing

Prof. Kim, 3 Credits


Marketingkommunikation

Prof. Kim, 4.5 Credits


Operations Research in Health Care Management

Prof. Nickel, 4.5 Credits


Ereignisdiskrete Simulation in Produktion und Logistik

Prof. Spieckermann, 4.5 Credits


Challenges in Supply Chain Management

Prof. Blackburn, 4.5 Credits


Semantic Web Technologies

Prof. Sure-Vetter, Prof. Studer, 5 Credits


Computational Economics

Prof. Shukla, 5 Credits


Energy Systems Analysis

Prof. Bertsch, 3 Credits


Krankenhausmanagement

Prof. Hansis, 3 Credits


Pricing

Prof. Kim, 4.5 Credits


Produktions- und Logistikcontrolling

Prof. Wlcek, 3 Credits


Digital Transformation of Organizations

Prof. Mädche, 4.5 Credits


Service Design Thinking

Prof. Satzger, 9 Credits


Foundations of Digital Services A

Prof. Satzger, Prof. Weinhardt, Prof. Sure-Vetter, 4.5 Credits


Service Oriented Computing

Prof. Studer, 5 Credits


Grundzüge der Informationswirtschaft

Prof. Weinhardt, 5 Credits


Industrial Services

Prof. Fromm, 4.5 Credits

Business and IT Service Management

Prof. Satzger, 4.5 Credits


Online Marketing

Prof. Kim, 4.5 Credits


Service Innovation

Prof. Satzger, 4.5 Credits


Market Engineering: Information in Institutions

Prof. Weinhardt, 4.5 Credits


Geschäftsmodelle im Internet: Planung und Umsetzung

Dr. Teubner, 4.5 Credits


Efficient Energy Systems and Electric Mobility

Dr. McKenna, Dr. Jochem, 3.5 Credits


Basics of Liberalised Energy Markets

Prof. Fichtner, 3.5 Credits


Mathematical Methods for Quantitative Finance

Prof. Konis, 6 Credits (8 weeks, 8-10 hours a week)


Gamification

Prof. Werbach, 4 Credits (6 weeks, 4-8 hours a week)


Marketing Analytics

Prof. Venkatesan, 2 Credits (5 weeks, 3-5 hours a week)


Enabling Technologies for Data Science and Analytics:
The Internet of Things

Prof. Chang, 4 Credits (5 weeks, 7-10 hours a week)


Statistical Thinking for Data Science and Analytics

Prof Gelman, Prof. Madigan, 4 Credits (5 weeks, 7-10 hours a week)


Predictive Analytics

Prof. Kumar, 3 Credits (7 weeks, 4-5 hours a week)


Innovation and IT Management

Prof. De’, 3 Credits (6 weeks, 4-6 hours a week)


Entrepreneurship 101: Who is your customer?

Mr. Aulet, 2 Credits (6 weeks, 4 hours a week)


Entrepreneurship 102: What can you do for your customer?

Mr. Aulet, 2 Credits (6 weeks, 4 hours a week)


Foundations of Data Analysis - Part 1: Statistics Using R

Mahometa Ph.D., 3 Credits (6 weeks, 3-6 hours a week)


Foundations of Data Analysis - Part 2: Inferential Statistics

Mahometa Ph.D., 3 Credits (6 weeks, 3-6 hours a week)


Culture of Services: New Perspective on Customer Relations

Prof. Yamauchi, 2 Credits (8 weeks, 2-3 hours a week)