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Business Analytics with Python: Pricing and Revenue Management

This course is fully booked (no waiting list)

In this course students will delve deep into the realm of Revenue Management using Python. Starting with an understanding of Python core functionalities and the basics of revenue management, we'll then shift our focus to descriptive analytics, where data handling and visualization come into play using Python tools like Pandas and Matplotlib to make sense of demand and revenue data. As we move to predictive analytics, participants will learn about demand forecasting using time series and machine learning techniques. With the foundation set, the course will dive into prescriptive analytics, exploring the nuances of dynamic pricing, price optimization, and capacity management. Practical aspects, such as simulating pricing strategies and data-driven decision-making, will be at the forefront. 

Exam info and full course description

Exam info and full course description can be found in the course catalogue.

Admission Requirements

Course specific:

A Bachelor’s degree in Business Administration or Business Economics or an equivalent degree. Fundamental concepts of programming (control and data structures) and quantitative methods (statistics, linear programming) will be expected, some basic economics / marketing 


Exchange students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about admission here.


Christoph Flath


Academic profile

Dr. Christoph Flath is a Professor of Information Systems and Business Analytics at Julius Maximilians University of Würzburg.