Siemens team wins
Artificial Intelligence will without any doubt change the way we will do business in future. As a matter of fact, it is already c hanging many businesses that we are involved in today. But what is needed to make Artificial Intelligence a valuable part of the way we do business ourselves? Many experts believe that successful Artificial Intelligence applications hinge on the so-called b-smact technologies (Blockchain, Social media, Mobile use, Analytics, Cloud and Things-on-the-internet or better known as IoT). The fuelling component of those technologies is Big Data.
After participating in this programme, you will be able to:
- Understand the foundations for becoming a data-driven organization, as a basis for exploiting insights from analytics and AI.
- Understand the complete data analytics lifecycle, from data exploration, data engineering, data analysis, data visualization up to presenting the insights.
- Discover new ways to apply data technologies to design and implement innovative and value creating business and societal applications.
- Improve both the business skills of technically focused data scientists and the capabilities of applying quantitative methods by those in business. Hereby mutual understanding is created, which supports the collaboration.
- Broaden data scientists’ and business members understanding of psychological factors, privacy, security, ethics and accountability and to stimulate critical thinking.
The programme uses a holistic approach by participation in multi-disciplinary and multi-hierarchical teams from various industries and a learning-by-doing approach from peers and via coaching by top academics and business experts.
|Length||14 modules and four coaching sessions spread over a period of 4 months.|
National and international company teams (three to six persons) from the following three domains in the organisation:
|Faculty||Taught by internationally renowned top scientists from Erasmus University Rotterdam, TU Delft, Leiden University and several guest speakers from businesses.|
|Certificate||Official certification by Rotterdam School of Management, Erasmus University and the Erasmus Centre for Data Analytics.|
The course is divided into four blocks to allow the application of the concepts learned.
Two days of preparation sessions, during which each participating company is expected to bring at least one case study to which the teams can apply the concepts they have learned. During this part of the programme, you will focus on the strategic importance of data-driven organisations, terminology, leadership challenges and readiness of companies, including their enterprise architecture and digitised platform. It includes case studies from other companies and short presentations from participating companies.
Two days including one evening session during which you explore the basic technology challenges of a data-driven company; technologies for analysis, prediction and visualisation. The evening session will focus on exchanging information and insights between the participants including a get to know each other social event with an academic touch.
Two days including one evening session during which you explore the basic management challenges of data-driven company; business cases, legal and privacy issues, change management and implementation. The evening session will focus on the company use case, consulting with both academic- and business coaches.
Two days for fine tuning the gained knowledge and turn it into applicable wisdom. Discuss challenges you have experienced in transforming your business and the implementation of your proposals. In the afternoon of the second day each team’s case study results will be presented to an expert panel and discussed in the class.
This programme is suited for company teams from data-intense industries with one or more data scientists and one or more business analysts working with business models and applications, as well as senior executives and supervisors. Professionals in non-profit organisations and governments, particularly those who work on smart city concepts, may also benefit.
Faculty members of RSM and ESE combine impeccable academic credentials with a thorough knowledge of business practice; they are listed below. Selected for their ability and experience in executive teaching, they will draw on their research and knowledge to deliver a unique learning experience. Occasionally we may substitute other faculty members according to the content of the programme and their availability.
Dr Rodrigo Belo
Rodrigo Belo is associate professor at RSM. His research focuses on the effects of information systems on organisations and on the impacts of social network structures and peer influence on consumer behaviour; it has been widely published. He specialises in the design and deployment of large-scale randomised experiments to assess the effectiveness of marketing campaigns, and to optimise online user engagement. He has led and collaborated in projects with established firms and start-ups in the online and telecommunications sectors. Before joining academia, Rodrigo worked as a software engineer and analyst in transportation and government.
Dr Dion Bongaerts
Dion Bongaerts is an associate professor of Finance at RSM. He specializes in credit markets and market liquidity. The use of innovative technologies in financial markets is of particular interest to him. His work has been presented at major conferences around the world, including the AFA, WFA, EFA, and NBER meetings and published in top tier academic journals including the Journal of Finance and Review of Financial Studies. He has received several grants, including a Veni grant from the Dutch National Science Foundation (NWO) and a Lamfalussy Fellowship from the ECB. Dr. Bongaerts holds a PhD degree in Finance from the University of Amsterdam, an MSc in Econometrics from Maastricht University and has been a visiting scholar at Yale School of Management. Moreover, he has several years of professional experience as a risk management quant at ABN-AMRO bank.
Dr Jan van Dalen
Jan van Dalen is an associate professor of statistics at RSM. He is the co-founder of the recently established Erasmus Centre for Data Science and Business Analytics, and co-director of E-Urban, and leads the Urban Big Data knowledge lab in collaboration with the City of Rotterdam. His main research interests are in quantitative analysis of information, logistics, trade and organisational processes, and he has been involved in research programmes that include monitoring trade and traffic flows with CBS, trade lane risk assessment in Cassandra, and cross-chain collaboration in 4C4More/Dinalog. He has extensive teaching experience in applied statistics, forecasting and big data in bachelor, master and executive teaching programmes.
Prof. Eric van Heck
Eric van Heck is a professor of information management and markets at RSM. His research concentrates on business architectures and digital platforms for dealing with complex societal and business challenges. At the moment he works on Auction Markets, Big Data & Analytics, Digital Business & Architecture, and Digital Work. Research is carried out in collaboration with innovative companies and universities in Brazil, China, Europe, Indonesia, and USA. He is an active member of the Erasmus Center for Data Analytics and the Erasmus Center for Future Energy Business.
Prof. Ting Li
Ting Li is a professor of digital business at RSM, and the academic director of the MSc Business Information Management programme, and of the Erasmus Centre for Data Analytics. Her teaching expertise covers information strategy, digital commerce, social and mobile analytics, and social networks. Before joining the academic world, she worked for General Electric and IBM in e‐business in supply chains, web services, and grid computing. Ting’s research interest focuses on the strategic use of information and its economic impacts on consumer behaviour and company strategy. She has worked with Shell, KPMG, PwC, Accenture, Coolblue, Wehkamp, Zelf, Tweakers, Shop2Market, Dutch Railways, and RET among others.
Prof. Gui Liberali
Gui Liberali is a professor of Digital Marketing at the RSM. Gui has successfully developed and applied methods for designing and customizing digital products and interactions, and adaptive online experimentation methods to online display advertising and website design, in research collaborations with firms in the U.S., U.K, and Europe. His work has been published in the most prestigious journals and has been cited in various technology blogs, magazines, and textbooks in marketing and operations research. Prof. Liberali holds a Doctorate in Marketing, and a B.Sc. in Computer Science. Gui was a visiting scholar at the MIT Sloan School of Management for several years. Gui is also Vice-President for Membership at the INFORMS Society for Marketing Science and an ERIM Fellow. He was awarded a two-year grant by the E.U for his research on recommendation systems.
Dr Iuliana Sandu
Iuliana Sandu is a lecturer in the department of Accounting & Control at RSM. She earned her master’s degree in Economics and Finance of Aging at Tilburg University, her master’s degree in Accounting, Audit and Management Information Systems and her PhD in Pension Fund Performance at the Bucharest University of Economic Studies. Her teaching activities relate to financial and management accounting topics. Her interests are in educational innovations, data analytics and accounting.
Prof. Peter Vervest
Peter Vervest is professor of information management and networks at RSM. His key research areas include decision science; network technologies and applications; business networks; competitive strategy; and change management. He joined Philips Telecommunications and Defense Systems in the early days of connecting computers to telecommunication networks, and has served on international standards and policy committees. He co-founded a high tech software and project firm in London, worked in public research and at KPN, the Dutch national telecom operator, and worked in managing early stage investment funds in Europe and Silicon Valley. He has published articles and books on the development and use of complex networks.
The Leadership Challenges with Data Analytics programme is a blended programme, with some modules delivered face-to-face and the others offered online via weekly interactive Zoom sessions. The programme is based on a combination of 14 modules with presentations, group activities and in class exercises and four use case coaching sessions. The programme features 3 lunches and a closing dinner.
The fee for each participants for the eight-day programme is € 8,500 (excl. VAT). This includes course materials, access to the e-learning platform, individual coaching during the programme, lunches, three dinners and social activities. Discounted rates apply and according to the number of participants per organisation, and are shown in the table below. For teams with more than five participants, each additional participant over five participants is € 7,000 (excl. VAT).
Number of participants Cost per participant Cost for partner organisation
1 € 8,500 € 8,500
2 € 8,000 € 16,000
3 € 7,500 € 22,500
4 € 7,250 € 29,000
5 € 7,000 € 35,000
Please contact us for more information: firstname.lastname@example.org.
Cancellation notices must be received by email: email@example.com. The following cancellation fees apply:
- More than 14 days before the programme’s start date: 25% of the programme fee will be charged
- Between 14 and 7 days before the programme’s start date: 75% of the programme fee will be charged
- 7 days or fewer before the programme’s start date: 100% of the programme fee will be charged
- Cancellations received on or after the programme’s start date: 100% of the programme fee will be charged.
The programme is offered as on-line programme. Some of the last modules might be offered at Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, Rotterdam (depending on Covid-19).
The programmes take place at Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, Rotterdam.
If you require hotel accommodation in Rotterdam, we recommend Novotel Rotterdam Brainpark, adjacent to the university.