5780 Blockchain Applications of Data Science
Dr. Claudio Di Ciccio, M.Sc.
Contact details
Weekly hours
Language of instruction
02/06/18 to 02/21/18
Registration via LPIS
Notes to the course
Day Date Time Room
Wednesday 05/16/18 01:30 PM - 05:30 PM TC.4.12
Wednesday 05/23/18 01:30 PM - 05:30 PM TC.4.12
Wednesday 05/30/18 01:30 PM - 05:30 PM TC.4.12
Wednesday 06/06/18 01:30 PM - 05:30 PM TC.4.12
Wednesday 06/13/18 01:30 PM - 05:30 PM TC.4.12
Wednesday 06/20/18 01:30 PM - 05:30 PM TC.4.12

The course gives an introduction into applications of data science in the fields of marketing and supply chain management. In this semester, we will focus on the understanding of, and developing on, the blockchain.

From a theoretical angle, basic concepts of distributed systems, hashing, and cryptography will be described. From a practical angle, the application of those concepts to the blockchain realm will be explained and applied hands-on. From an implementation viewpoint, special interest will be devoted to Ethereum, Solidity smart contracts, and DApps.

Learning outcomes

After completing this course students will have knowledge about different areas of application for data science. Students will have a basic understanding of area specific challenges and algorithms.

In this semester, students will learn about recent applications of data science and business process management on the blockchain. Besides an understanding of the blockchain rationale and aims, students will learn to design and implement automated systems based on the blockchain that support business processes. Apart from that, completing this course will contribute to the students’ ability to efficiently work and communicate in a team, work on solutions for complex practical problems by using cutting-edge technologies.

Teaching/learning method(s)
The course will combine alternative ways to deliver the different topics to the students. On the one hand, a classical lecture style approach where the instructor presents the software and the content will be used; on the other hand, students will have to solve hands-on problems in class and as homework.

The students will take part in continuous project work. The final grade of the course will depend as follows on homework assignments, research report, and final presentation:

  • 50% homework assignment
  • 30% research report
  • 20% final presentation.
Prerequisites for participation and waiting lists

Successful conclusion of the course 1 of SBWL Data Science.

Please be aware that, for all courses in this SBWL, registration is only possible for students who successfully have completed the entry course (Einstieg in die SBWL: Data Science). Note that for courses within the SBWL "Data Science" we can only accept students enrolled in one of WU's bachelor programmes who qualify for starting an SBWL; particularly, we cannot accept students from other courses and programmes enrolled at WU as 'Mitbeleger' only.

Recommended previous knowledge and skills

Basic understanding of programming is recommended.

Availability of lecturer(s)

Please contact the lecturer via e-mail to fix an appointment.

Last edited: 2017-12-14