Emerging Technologies in Digitalisation

  • Teaching

    Details

    Faculty Faculty of Management, Economics and Social Sciences
    Domain Information Systems
    Code UE-EIG.00169
    Languages English
    Type of lesson Lecture
    Level Master
    Semester SP-2021

    Schedules and rooms

    Summary schedule Wednesday 09:15 - 12:00, Hebdomadaire, PER 21, Room B207
    Hours per week 3

    Teaching

    Responsibles
    Teachers
    Assistants
    Description

    In this course we will investigate emgerging technologies in the area of digitalization of enterprises such as blockchains and smart contracts, augmented and virtual reality, data warehouses, machine learning platforms, semantic technologies and others. The concrete range of technologies will be announced at the beginning of the course. The goal is to conduct explorative research on the characteristics of these technologies and the resulting opportunities for business applications.

    For this purpose, small projects will be conducted in teams for analyzing particular usage scenarios for the technologies, designing according solutions using techniques of conceptual modeling and implementing them in the form of prototypes. Following lectures for introducing the foundations of the technologies, students will set up their own projects and regularly report upon the advancement in the projects in the form of common presentations. At the end, final presentations of the projects including working prototypes and the submission of a seminal report based on scientific standards are required. For the implementation of the prototypes it is necessary to dispose of programming knowledge, e.g. in Java, Node.js, or Python.

    Moodle Link

    Training objectives

    The goal of this course is to get a fundamental understanding of common technologies in the context of digitalization of enterprises and being able to create according software applications. Further, the writing of seminal papers is trained for preparing students to conduct their own research as e.g. required for master and doctoral theses.

    Softskills
    No
    Off field
    No
    BeNeFri
    Yes
    Mobility
    Yes
    UniPop
    No

    Documents

    Bibliography

    * Narayanan, Arvind, Clark, Jeremy (2017): Bitcoin's Academic
    Pedigree. ACMQueue, Volume 15, issue 4.
    https://queue.acm.org/detail.cfm?id=3136559

    * Antonopoulos, Andreas M., Wood, Gavin (2018): Mastering Ethereum.
    O’Reilly. https://github.com/ethereumbook/ethereumbook

    * Hyperledger Fabric (2020): Documentation.
    https://hyperledger-fabric.readthedocs.io/en/release-2.2/whatis.html

    * Three.js Documentation (2020): https://threejs.org/docs/

    * KNIME Analytics Documentation (2020): https://docs.knime.com/

    * RapidMiner Educational License Program (2020):
    https://rapidminer.com/educational-program/

    * R Platform Manuals (2020): https://cran.r-project.org/manuals.html

    * Protégé Documentation (2020):
    https://protegewiki.stanford.edu/wiki/Main_Page

  • Dates and rooms
    Date Hour Type of lesson Place
    24.02.2021 09:15 - 12:00 Cours PER 21, Room B207
    03.03.2021 09:15 - 12:00 Cours PER 21, Room B207
    10.03.2021 09:15 - 12:00 Cours PER 21, Room B207
    17.03.2021 09:15 - 12:00 Cours PER 21, Room B207
    24.03.2021 09:15 - 12:00 Cours PER 21, Room B207
    31.03.2021 09:15 - 12:00 Cours PER 21, Room B207
    14.04.2021 09:15 - 12:00 Cours PER 21, Room F207
    21.04.2021 09:15 - 12:00 Cours PER 21, Room B207
    28.04.2021 09:15 - 12:00 Cours PER 21, Room B207
    05.05.2021 09:15 - 12:00 Cours PER 21, Room B207
    12.05.2021 09:15 - 12:00 Cours PER 21, Room B207
    19.05.2021 09:15 - 12:00 Cours PER 21, Room B207
    26.05.2021 09:15 - 12:00 Cours PER 21, Room B207
    02.06.2021 09:15 - 12:00 Cours PER 21, Room B207
  • Assessments methods

    Examen écrit - SP-2021, Session de rattrapage 2021

    Assessments methods By rating
    Descriptions of Exams

    Exam lenght: 90 minutes

    Only as a retake exam

    Evaluation continue - SP-2021, Session d'été 2021

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Branche secondaire Master: informatique de gestion 30 [MA]
    Version: 2020/SA_V01
    Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization

    Business Communication - Information Systems 90 ECTS [MA]
    Version: 2020/SA_V01
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization

    Data Analytics 30 [MA]
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization

    Information Management 90 ECTS [MA] - SA/2019
    Version: 2019/SA_V01
    Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization

    Information Management 90 ECTS [MA] - SA/2020
    Version: 2020/SA-v01
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for Digitalization

    MSc in Computer science (BeNeFri)
    Version: 2010_2/V_02
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T5: Information Systems and Decision Support