Emerging Technologies in Digitalisation
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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-2022 Schedules and rooms
Summary schedule Wednesday 08:15 - 10:00, Hebdomadaire (Spring semester)
Wednesday 10:15 - 11:00, Hebdomadaire (Spring semester)
Hours per week 3 Teaching
Responsibles - Fill Hans-Georg
Teachers - Fill Hans-Georg
Assistants - Härer Felix
- Muff Fabian
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.
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 23.02.2022 08:15 - 10:00 Cours PER 21, Room F207 23.02.2022 10:15 - 11:00 Exercice PER 21, Room F207 02.03.2022 08:15 - 10:00 Cours PER 21, Room F207 02.03.2022 10:15 - 11:00 Exercice PER 21, Room F207 09.03.2022 08:15 - 10:00 Cours PER 21, Room F207 09.03.2022 10:15 - 11:00 Exercice PER 21, Room F207 16.03.2022 08:15 - 10:00 Cours PER 21, Room F207 16.03.2022 10:15 - 11:00 Exercice PER 21, Room F207 23.03.2022 08:15 - 10:00 Cours PER 21, Room F207 23.03.2022 10:15 - 11:00 Exercice PER 21, Room F207 30.03.2022 08:15 - 10:00 Cours PER 21, Room F207 30.03.2022 10:15 - 11:00 Exercice PER 21, Room F207 06.04.2022 08:15 - 10:00 Cours PER 21, Room F207 06.04.2022 10:15 - 11:00 Exercice PER 21, Room F207 13.04.2022 08:15 - 10:00 Cours PER 21, Room F207 13.04.2022 10:15 - 11:00 Exercice PER 21, Room F207 27.04.2022 08:15 - 10:00 Cours PER 21, Room F207 27.04.2022 10:15 - 11:00 Exercice PER 21, Room F207 04.05.2022 08:15 - 10:00 Cours PER 21, Room F207 04.05.2022 10:15 - 11:00 Exercice PER 21, Room F207 11.05.2022 08:15 - 10:00 Cours PER 21, Room F207 11.05.2022 10:15 - 11:00 Exercice PER 21, Room F207 18.05.2022 08:15 - 10:00 Cours PER 21, Room F207 18.05.2022 10:15 - 11:00 Exercice PER 21, Room F207 25.05.2022 08:15 - 10:00 Cours PER 21, Room F207 25.05.2022 10:15 - 11:00 Exercice PER 21, Room F207 01.06.2022 08:15 - 10:00 Cours PER 21, Room F207 01.06.2022 10:15 - 11:00 Exercice PER 21, Room F207 -
Assessments methods
Written exam
Assessments methods By rating Descriptions of Exams Exam lenght: 90 minutes
Only as a retake exam
Evaluation continue - SP-2022, Session d'été 2022
Assessments methods By rating Descriptions of Exams Course with continuous evaluation: after the registration period, you can no longer cancel your registration (see session calendar on the Faculty's website).
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Assignment
Valid for the following curricula: Additional Courses in Sciences
Version: ens_compl_sciences
Paquet indépendant des branches > Specialized courses in Computer Science (Master level)
Additional programme requirements for PhD studies [PRE-DOC]
Version: 2020_1/v_01
Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)
BeNeFri - Sciences économiques et sociales
Version: 2018/SP_V01_SES_BeNeFri
Course > Master course offering for BeNeFri Students
Complementary learnings in SES or mobility students
Version: ens_compl_ses
Mster course offering for Mobility Students
Computer Science [3e cycle]
Version: 2015_1/V_01
Continuing education > Specialized courses in Computer Science (Master level)
Computer Science [POST-DOC]
Version: 2015_1/V_01
Continuing education > Specialized courses in Computer Science (Master level)
Doc - Business Informatics
Version: 20210713
Elective courses > Wahlkurse UNIFR
Doc - Economics
Version: 2002/SA_V01
Cours a choix > Wahlkurse UNIFR
Doc - Economie quantitative
Version: 2002/SA_V01
Cours a choix > Wahlkurse UNIFR
Doc - Management
Version: 2002/SA_V01
Cours a choix > Wahlkurse UNIFR
Doc - Management in Nonprofit-Organisation
Version: 2002/SA_V01_60ECTS Théoriques
Elective courses > Wahlkurse UNIFR
Doc - Sciences sociales
Version: 2002/SA_V01
Cours a choix > Wahlkurse UNIFR
Doc - Sciences économiques et sociales
Version: 2002/SA_V01
Cours a choix > Wahlkurse UNIFR
Ma - Accounting and Finance - 90 ECTS
Version: 2021/SA_V01
Course - 72 ECTS > Minimum 0 / maximum 1 optional master course offered at the University of Fribourg, if 72 ECTS not yet reached in the above modules > SES Master level courses
Ma - Business Communication : Business Informatics - 90 ECTS
Version: 2020/SA_V02
Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for DigitalizationCourses - 60 ECTS > Option Group > Information Management > Cours > Module Informatik > Advanced Software Engineering
Ma - Business Informatics - 90 ECTS
Version: 2020/SA-v01
Classes - min. 45 ECTS > Module IT and IT Management > Advanced Software EngineeringClasses - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for DigitalizationClasses - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
Ma - Communication and Media Research - 90 ECTS
Version: 2015/SA_V01
Courses - 60 ECTS > Inter- and Transdisciplinary Perspectives > SES Master level courses
Ma - Communication and Society - 90 ECTS
Version: 2021/SA_V03
Forschungsbereiche > Inter- & Transdisciplinary Perspectives
Ma - Economics - 90 ECTS
Version: 2021/SA_V04
Le choix de l'option se fait par l'inscription au premier cours dans l'une des options possibles. > Public Economics and Policy > Elective courses in Public Economics and Policy > Elective courses of the SES Faculty - max. 15 ECTS > SES Master level coursesLe choix de l'option se fait par l'inscription au premier cours dans l'une des options possibles. > Business Economics > Elective courses in Business Economics > Wahlkurse der SES-Fakultät - max. 15 ECTS > SES Master level coursesLe choix de l'option se fait par l'inscription au premier cours dans l'une des options possibles. > Sustainable Development and Social Responsibility > Elective courses in Sustainable Development and Social Responsibility > Elective courses of the SES Faculty - max. 15 ECTS > SES Master level coursesLe choix de l'option se fait par l'inscription au premier cours dans l'une des options possibles. > Quantitative Economics > Elective courses in Quantitative Economics > Courses from the SES faculty - max. 15 ECTS > SES Master level coursesCourse selection for the Master WITHOUT options > Elective courses > Elective courses of the SES Faculty - max. 15 ECTS > SES Master level courses
Ma - European Business - 90 ECTS
Version: 2017/SA_v01
Courses - 63 ECTS > Additional courses: Any Master courses of the Faculty of Economics and Social Sciences, as well as maximum 9 ECTS from all Master programmes of the University. > SES Master level courses
Ma - Information Management - 90 ECTS
Version: 2019/SA_V01
Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for DigitalizationClasses - min. 45 ECTS > Module IT and IT Management > Advanced Software EngineeringClasses - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
Ma - International and European Business - 90 ECTS
Version: 2021/SA_V01
Courses > Additional courses: Any Master courses of the Faculty of Economics and Social Sciences, as well as maximum 9 ECTS from all Master programmes of the University. > SES Master level courses
Ma - Management - 90 ECTS
Version: 2021/SA_V01
Courses: min. 72 ECTS > Elective Courses : max. 18 ECTS > SES Master level courses
Ma - Management - 90 ECTS [MA]
Version: 2017/SA_v01
Courses: min. 63 ECTS > Cours facultatifs : max. 18 ECTS > SES Master level courses
Ma - Marketing - 90 ECTS
Version: 2021/SA_V02
Courses > Elective Master courses from the whole university > SES Master level courses
MiMa - Business Informatics - 30 ECTS
Version: 2020/SA_V01
Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for DigitalizationCours > Module Informatik > Advanced Software Engineering
MiMa - Data Analytics - 30 ECTS
Version: 2020/SA-v01
À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization