Digitalization is leading to rapid growth in data volumes, for example from social networks or the Internet of Things. Data science - these are the technologies and the special knowledge needed to generate added value from this inexhaustible potential. Companies are recognizing the strategic importance of data science.
But what business model can be used to realize the potential of data science for process improvements and product and service innovations? And how can bad investments be avoided in the unmanageable market of technical solutions for storing, managing and analyzing data volumes?
The certificate course presents the potential of data science for companies and the hurdles that currently exist. Participants' individual questions will be discussed with the university teacher / lecturer and experienced peers.

Upon successful completion of the course, you will be able to

• Classify frameworks for the use of data science technologies.
• Explain architectures and data science technologies.
• Discuss various application scenarios for the use of data science analyses.
• Understand the basic principles of data-driven business models.
• Know the process model and success factors for implementing data science projects.
• Evaluate the opportunities and risks of data science analyses.
• Determine the cost-effectiveness of data science technologies.

• You will learn about data science technologies to develop data-driven business models and improve operational decision-making processes.
• You will learn about realistic application scenarios and practical examples of data science analyses.
• By working on an individual question on the use of a data science technology, direct practical transfer is guaranteed.
• You benefit from individual support and intensive exchange in small groups.

The certificate course is aimed at decision-makers, managers and prospective managers, project managers, business developers and IT experts in data science projects across all industries and sectors...

• who want to apply the basic principles of data-driven business models
• who want to understand the use of data science technologies
• who want to identify different application scenarios when using data science analyses
• who are involved in the implementation of the digitalization of business models and in particular of data science projects or would like to lead them in a targeted manner.

The interactive seminar-style course offers the opportunity to address individual questions and problems posed by participants. Exercises are offered for each block of knowledge. An online learning platform supports learning success. The project assignment with presentation of results enables direct transfer into practice.

• Dates: Three ONLINE presence days on request at weiterbildung(at)hsnr.de
• Registration deadline: ---
• Number of participants: approx. 12 persons
• Location: Online format (Zoom meeting)
• Course language: The certificate course is held in German.

• Participation fee: 990 € | alumni (5% discount) 940 €
• Participation requirements: University degree with one year of professional experience or vocational training and at least three years of professional experience
• Scope (workload): 75 h, of which attendance 24 h, 3 ECTS
• Degree: University certificate / certificate of attendance.
  Participants receive a certificate of attendance if at least 75% of the course is attended. A certificate from The Hochschule Niederrhein is awarded upon passing the examination.

Three questions for your university teacher / lecturer, Prof. Dr. Uwe Schmitz:
Why is continuing education in "Data Science Potentials" currently of interest to many professionals?
"A large amount of mass data is generated every day, both in our private and professional lives. Processing and analyzing this data can not only lead to significant improvements in business processes and decision-making in all functional areas of a company, but also to new data-driven business models."

What are you particularly looking forward to on this university certificate course?
"The contact with practitioners who are active in this context or are planning to invest in this area."

And what can participants look forward to?
"To learning about topics with a practical emphasis / orientation."