Business Engineering

A study programme with the Business Engineering profile enables students to develop, produce and distribute innovative products and services, as well as to improve processes and business models. Students take account of quality, risk management and life cycle aspects and are able to make targeted use of management information systems, tools that provide support during decision-making processes and quantitative methods for the analysis of business and production processes, markets and customers.

Further information on the MSE in Business Engineering

Data Science

The MSE in Data Science is based on the three pillars of Data Engineering, Data Analytics and Data Services. At the IDP, you have the opportunity to specialise in Data Analytics and Data Services. In Data Analytics, the focus is placed on the application of statistical data analysis, as well as machine and deep learning. The Data Services focus area involves dealing with challenges or improving the situation in companies by using data-driven services and developing such services.

MSE students at the IDP are personally supervised by senior scientists and can choose from a wide range of topic areas:

• Data Science in Finance (Christoph Schmidhuber)
• Blockchain and Distributed Ledger (Christian Badertscher)
• Data Science in Mobility (Raimond Wüst)
• AI for Machines and Infrastructures (Lilach Goren)
• AI-based Service Engineering (Jürg Meierhofer)
• Responsible AI: Ethical algorithms and Fair Machine Learning (Christoph Heitz)
• Survey Data Analysis (Reto Bürgin)
• Data Analysis in Actuarial Science (Anna Drewek, Thoralf Mildenberger, Andreas Ruckstuhl)
• Data Analysis in Operational and Business Applications (Anna Drewek, Christoph Hofer, Thoralf Mildenberger)
• Interpretable AI and Biostatistics (Beate Sick)
• Machine Learning in Visual Computing (Helmut Grabner)
• Predictive Analytics and Forecasting (Marcel Dettling) 
• Sports Analytics and Tracker Data (Martin Frey)

MSE students at ZHAW have the opportunity to work as scientific assistants alongside their studies and thus participate to research projects. Contact us if you are interested in collaborating with us.

Module

In the module browser, you can find the central modules (context modules [CMs], extended fundamental theoretical principles [FTPs] and technical scientific specialisation modules [TSMs]).

The institute (in some cases on an inter-institute basis) also offers the following decentralised specialisation modules (EVA):

• IDP Methodology Seminar (2 ECTS credits)
• Artificial Intelligence Seminar (2 ECTS credits)
• Machine Intelligence (4 ECTS credits)
• Individual wishes are also taken into account in consultation with the respective supervisor (e.g. online course; independent work on a book, paper, etc.; courses at other universities)

MSc theses

• Application of deep learning methods in the fields of medicine, predictive maintenance and quality assurance
• Predictive modelling for demand and sales forecasts and in business analytics
• Analytics in the sports sector
• Customer segmentation and analysis and forecasting of customer behaviour patterns
• Application of data science methods in the areas of finance, insurance and economics
• Development of innovative methods for the design of data-driven services or smart products