Overview
Next Steps
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Data Science
Business impact through effective data handling
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.
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Schedule
- Module 1: What is Data Science? Concepts & Application Domains (4 Days)
September 26 - 29, 2018 - Module 2: From Data Science to Big Data (4 Days)
November 14 - 17, 2018 - Module 3: Data Science in Practice and in the Future (4 Days)
January 23 - 26, 2019
- Module 1: What is Data Science? Concepts & Application Domains (4 Days)
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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).
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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
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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 mostly.ai 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.
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Certificate
After completing the course, you will receive a certificate including course details from the WU Executive Academy.
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Faculty
Axel Polleres
Professor and Head of Institute | Department of Informations Systems & Operations | Institute for Information Business | WU Vienna | Austria
Claudio Di Ciccio
Assistant Professor | Institutes for Management Information Systems & Operations and Information Business | WU Vienna
- Process mining
- Declarative process modeling
- Complex event processing
Ronald Hochreiter
Lecturer | Institute of Statistics and Mathematics | WU Vienna | Austria
Sabrina Kirrane
Assistant Professor | Institutes for Management Information Systems & Operations and Information Business | WU Vienna
- Digital forensics
- Data analytics
- Semantic web and linked data
Jan Mendling
Deputy Head of Department | Institute of Information Business | WU Vienna | Austria
Andreas Mild
Deputy Head of Institute | Production Management | WU Vienna
- 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
Thomas Reutterer
Head of Institute | Service Marketing and Tourism | WU Vienna
- Retail and service marketing
- Customer value management
- Marketing models for customer-base analysis and decision support
Elena Simperl
Professor | Computer Science | University of Southampton | United Kingdom
Alfred Taudes
Professor | Department of Information Systems and Operations | WU Vienna | Austria
