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Data Science
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.
Take 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!
Maria Molchanova
- Customer Experience & Marketing Lead for CEE & Germany | Roche Diabetes Care | mySugr GmbH
The 'Data Science' course gave me a holistic understanding of the field and showed me how it can be used practically in various business areas. As a senior marketing professional, it was crucial for me to see real-life examples of how companies can adjust their structures and mindset to become more data-driven. Learning about the latest advancements in AI was especially fascinating, as it showed how technology can enhance the work we do in organizations.
What you will learn:
✓ Gain a common understanding of the potential use of data and how it can be used effectively and efficiently.
✓ Be familiar with the contemporary methods and tools of data science, data analytics and machine learning
✓ Get relevant know-how to set up a data science project from scratch
✓ Work through real-life case studies with datasets from different domains
✓ Learn about current trends in AI and the AI Act
✓ Bridge the gap between understanding the business challenges and technical solutions
Schedule
- Module 1: The Data Science Process (4 days, 8:30-6:00pm)
November 6-9, 2024 - Module 2: Data Science at Work: Challenges & Solutions (4 days, 8:30-6:00pm)
December 11-14, 2024 - Module 3: Leveraging Data Science for Digital Transformation (4 days, 8:30-6:00pm)
February 19-22, 2025
- Module 1: The Data Science Process (4 days, 8:30-6:00pm)
Target Group
Data Science permeates all areas of business and all hierarchical levels.
You are…
- an analyst, product manager, expert from the technical field, executive or a professional who want to acquire a technical expertise to optimize the use of data within their organization.
- aiming at building a solid understanding of the data science process.
- interested in gaining insights about current trends in AI.
- eager to learn how to set up a data science project from scratch.
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).
No coding skills required.
Program Content
Module 1: The Data Science Process | 4 days
- Data analytics with Python & R
- Data management & data processing
- Data science lifecycle
Module 2: Data Science at Work: Challenges & Solutions | 4 days
- Data science project kick-off
- Legal and ethical foundations (incl. AI Act)
- Natural language processing & AI
- Digital Experimentation
Module 3: Leveraging Data Science for Digital Transformation | 4 days
- Advanced data analytics
- Data visualization & storytelling
- Data science project presentations
Certificate
After completing the course, you will receive a certificate including course details from the WU Executive Academy.
David Lindner
- Marketing & Export | Traktorenwerk Lindner GmbH
Before the course big data seemed to be far away from my daily business in a small sized company. I categorized this topic to be important for big global players – I was wrong. Now not only that I have realized that I need to deal with big data issues, but I also feel competent enough to handle big data projects in my company.
Faculty
Verena Dorner
Head of Institute for Digital Ecosystems | Academic director of the Master's Program on Digital Economy | Member of the WU Competence Center for Experimental Research | WU Vienna | Austria
Sabrina Kirrane
Assistant Professor | Institute for Information Business | member of the Institute for Cryptoeconomics | WU Vienna
- Digital forensics
- Data analytics
- Semantic web and linked data
Ted Kwartler
Managing Director North American Responsible AI, Accenture & Adjunct Faculty Harvard Extension School
- Data science & NLP
- Author of multiple analytical textbooks & contributed chapters
Gal Oestreicher-Singer
Professor & Associate Dean of Research | Department of Management of Technology and Information Systems | Tel Aviv University | Israel
Liuhuaying Yang
Data Visualization Researcher & Faculty | Complexity Science Hub | Austria
Fast-track your MBA journey
Would you like to dive deeper into the subject of digitization? Apply for the Executive MBA Digital Transformation & Data Science and attend e.g. the Data Science program in course of the part-time Executive 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
Did you know that you can receive the "Digi-Winner" grant up to € 5,000 for this program? The "Wiener Arbeitnehmer*innen Förderungsfonds (Waff)" is subsidizing this program. More information and conditions on the grant.
"Digital Skills Check" Grant
Small and medium-sized enterprises (SMEs) based in Austria can apply for funding of up to € 5,000 per employee with the "Digital Skills Check" from the Austrian Research Promotion Agency. Further information and all requirements for funding (in German).
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