Data Science

ⓘ Covid-19: Currently, we are offering modules in a hybrid format whenever possible, i.e. in-class teaching with simultaneous online participation for those students who are facing travel restrictions.


Become a pathfinder in the maze of big data and learn how to lead your company to outstanding success.

In times of digitalization, where buzzwords such as business intelligence (BI) and marketing automation are omnipresent, companies are confronted with huge challenges: how can they optimize their decision-making-process on the basis of an unimaginable mass of data, originating from a variety of sources? The answer lies in data science. To meet this need WU's executive academy has designed a cutting edge program on data science. In just a few months, you will get to know the tools, techniques, and fundamental concepts that you need to know in order to make an impact as a data scientist. You will learn how to unleash the potential of unused data resources within your enterprise - and how to approach this. During the course of the program, you will work through real-life case studies, with datasets from different domains (e.g. marketing, supply chain management) and will gain experience across the entire data science process: explorative data analysis, data munging, modelling, validation and cleansing, visualization, and communication.

Taking your skills to the next level

This applied program takes your data skills to the next level, shows you how to build big data pipelines as well as analytics processes and how to apply what you have learned in the context of real projects. At the end of the program, you will be able to apply all the methods dealt with and will have gathered an overview about the opportunities that open up as a data scientist. “Data Science” will guide you and your company to the future and provide you with the knowledge and skills necessary to be your organization’s data scientist. Help your company to get on the fast lane – master the big data challenge!

Become part of the WU community.

    • Schedule

      • Module 1: What is Data Science? Concepts & Application Domains (4 days)
        October 20-23, 2021
      • Module 2: From Data Science to Big Data (4 days)
        December 1-4, 2021
      • Module 3: Data Science in Practice and in the Future (4 days)
        February 23-26, 2022
    • Target Group

      This applied program is for analysts, product managers, business managers or simply someone who wants to optimize their and their companies’ decision making through data science. Participants come from a wide range of industries including:

      • Marketing, CRM, Business Analysis, Market Research
      • Consulting
      • Industry, Supply Chain Management, Manufacturing
      • Health Care, Pharma
      • Technology, IT, Telecommunications
      • Consumer Goods
      • Finance, Insurance

      Please note: You should have at least 3 years of work experience and a good command of English (as this is the language of instruction).

    • Topics

      Module 1: What is Data Science? Concepts & Application Domains | 4 days

      • Overview and case studies from different application domains (e.g. Marketing, Supply-Chain/Production Management, Process Management, Finance)
      • Data Processing and Data Analytics: Concepts & Methods
      • Selected case studies in depth

      Module 2: From Data Science to Big Data | 4 days

      • Data Science project kick-off
      • Legal and ethical foundations and data security
      • Big Data methods and algorithms
      • Data workflows, distribution, advanced techniques (e.g. Semantic Technologies, text extraction)
      • Commercial Data Science Tools Fair
      • Advanced Data Analytics

      Module 3: Data Science in Practice and in the Future | 4 days

      • Data processing and data analytics trends and outlook
      • Application of Data Science
      • Special guest talks by distinguished academic speakers and experienced experts from practice
      • Data Science project presentations
    • Academic Director

      Academic Director

      Axel Polleres

      Head of Institute, Information Business, WU Vienna

      • Logic programming
      • Semantic web technologies
      • Linked open data
      • Querying and reasoning about ontologies
      • Rules languages

      (Potential) External Speakers

      Elena Simperl Elena Simperl is a professor of Computer Science in the Web and Internet Science research group in the department of Electronics and Computer Science at the University of Southampton, UK since 2012. She received her doctoral degree in Computer Science from Freie Universität Berlin as well as a diploma in Computer Science from TU München. She has held numerous research and teaching positions at TU München, Freie Universität Berlin, STI Innsbruck and at the AIFB at the Karlsruhe Institute of Technology (KIT). Her research focuses on the intersection between knowledge technologies, social computing and crowdsourcing and she has published more than 100 scientific papers in various renowned journals. Philippe Cudré-Mauroux As a full professor at the University of Fribourg (Switzerland), he is in charge of the eXascale Infolab. Before that, he worked with Database Systems lab at MIT. He received his bachelors degree from EPFL and his two master degrees from Eurecom and fron INRIA SOP (University of Sofia-Antipolis). After working at IBM T.J. Watson Research, he went on to get his Ph.D. degree from EPFL (dissertation on emergent semantics). He worked as a visiting scholar at U.C. Berkeley and at Microsoft Research Asia, working on sensor data and novel information-sharing respectively. His research interests range from exascale information management to big data, scientific data and linked data. Michael Platzer Michael Platzer received a Ph.D. with a focus on Marketing Science from WU Vienna and earned an MSc in Mathematics (with distinction) from TU Vienna. He was a founding partner & CTO at Knallgrau New Media Solutions and a former data science lead at Nokia and Microsoft. He is founder and data scientist at and helps companies to leverage latest advances in machine learning and artificial intelligence for building smart data-powered solutions, with a solid understanding of product and service design.

    • Participant's Experience

      Data Science was a revelation for me. Before the program, I categorized big data to be exclusively important for big global players – I was wrong. Not only have I realized that I need to deal with my small business’ data, but I also feel competent enough to manage future challenges in my business. David Lindner

    • Certificate

      After completing the course, you will receive a certificate including course details from the WU Executive Academy.


Axel Polleres

Professor and Head of Institute | Department of Information Systems & Operations | Institute for Information Business | WU Vienna | Austria

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Claudio Di Ciccio

Claudio Di Ciccio

Assistant Professor | Institute for Information Business | member of the Institute for Cryptoeconomics  | WU Vienna

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- Process mining
- Declarative process modeling
- Complex event processing

Ronald Hochreiter

President & CEO | Academy of Data Science in Finance | Austria

Lecturer | Research Institute for Computational Methods | WU Vienna | Austria

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Sabrina Kirrane

Sabrina Kirrane

Assistant Professor | Institute for Information Business | member of the Institute for Cryptoeconomics | WU Vienna

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- Digital forensics
- Data analytics
- Semantic web and linked data

Mendling Jan Portrait

Jan Mendling

Department of Computer Science | Humboldt-University of Berlin | Germany &

Department of Information Systems and Operations | WU Vienna | Austria

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Andreas Mild

Deputy Head of Institute | Production Management | WU Vienna

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- Quantitative models in marketing and new product development

- Application of forecasting methods and decision support systems in the field of revenue management

- Application of prediction markets

Siegfried Handschuh

Professor of Data Science | Director of Institute of Computer Science | University of St. Gallen

Thomas Reutterer

Thomas Reutterer

Head of Institute | Service Marketing and Tourism | WU Vienna

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- Retail and service marketing
- Customer value management
- Marketing models for customer-base analysis and decision support

Alfred Taudes

Professor | Department of Information Systems and Operations | WU Vienna | Austria

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Harald Trautsch

Co-founder and CEO of Dolphin Technologies | Pioneer in the vehicle telematics industry

Fast-track your MBA journey

Would you like to dive deeper into the subject of digitization? Apply for the MBA Digital Transformation & Data Science and attend e.g. the Data Science program in course of the part-time Master of Business Administration. You can also get credit for a continuing education program that has already been completed at WU Executive Academy.

"Digi-Winner" Grant

Digi-Winner Logo

Did you know that you can receive the "Digi-Winner" grant up to € 5,000 for this program? The "Wiener ArbeitnehmerInnen Förderungsfonds (Waff)" is subsidizing this program.More information and conditions on the grant.

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