• Students will study the concepts of regression and classification problems (supervised learning) as well as principal components and clustering (unsupervised learning).
• In parallel, they will learn how to work with financial data with all its pitfalls, cover univariate and multivariate time series models of the mean and volatility and correlations, as well as model long-run relationships.

Lecture

• Students understand and can apply simple and multiple linear regressions as well as corresponding diagnostic tests.
• Students understand the pitfalls related to financial time series and know the corresponding methods and tools to overcome them.
• Students understand the concepts of supervised and unsupervised learning, can give examples and apply such methods to financial datasets.
• Students understand when to use univariate end multivariate time series models, know how to test and implement them and can interpret the output of such models.
• Students can explain co-integration and how it relates to univariate stationarity and apply the necessary testing algorithms.
• Students understand and know how to implement models of univariate and multivariate volatility.

• Developing research questions and hypothesis
• Designing qualitative and quantitative research
• Writing and communicating research proposals

Seminar

• Students conduct structured literature reviews and identify research gaps.
• Students derive research questions and testable hypotheses, motivated on the basis of existing literature.
• Students select and apply appropriate methods to answer the hypotheses.
• Students will produce rigorous research proposals in the area of finance.
• Students will effectively communicate academic research proposals.

The thesis process starts immediately after the deadline of the Exposé.

In Project Seminar, students analyse a real-world case from a specific industry. Students divide into groups according to their preferences and work on one of four cases through the lens of process management, data and application security, data science, or digital innovation. The course topics change from semester to semester.

• The course involves interactive seminars with workshops and regular presentations.
• The faculty and a jury of representatives from regional companies evaluate the students' solutions in terms of innovativeness and usefulness and provide them with feedback and advice.
• The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.

After successful completion of the course, students will be able to:

• analyse real-world cases
• collect and prepare data for analysis
• build and evaluate statistical models
• integrate areas of knowledge to identify areas of improvement or innovation
• use appropriate methods to develop recommendations for a case company

• The students are provided with all lecture slides and supporting materials.

Seminar paper, presentations, project results; attendance is mandatory (80%)

Process Mining covers conceptual foundations, methods, and technologies for analysing business processes with the help of digital trace data that stems from information technology. In particular, students learn how to mine digital trace data. The course focuses on three primary topics:

• Petri-net foundations of process analysis
• Process mining algorithms
• Process mining tools and applications

• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
• The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.

After successful completion of the course, students will:

• understand the foundational concepts of process mining
• understand how process mining algorithms work
• understand how a process mining project can be conducted in practice

Compulsory reading:

• Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. (2018). Fundamentals of Business Process Management (2nd edition). Berlin, Germany: Springer.

Additional reading:

• Van der Aalst, W. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes. Berlin, Germany: Springer.

Written exam (60min)

Network and System Security covers advanced security mechanisms in computer networks and systems and attacks against information systems. The course focuses on eight primary topics:

• Essential network-security protocols
• Attacks against common network protocols
• Security issues in web applications
• Security mechanisms in operating systems
• Advanced exploitation techniques

• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
• The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
• Lab exercises and programming assignments are used to support the acquisition of practical skills.

After successful completion of the course, students will:

• understand the typical attacks against various components of information systems
• understand the main network security protocols and their implementation
• understand the main preventive security mechanisms in operating systems

Technical documentation of the attacks and protection methods presented are provided.

Voraussetzung für die Anmeldung zum Modul:

• erfolgreicher Abschluss des Moduls "Data and Application Security"

Exercise: Lab assignments
Lecture: Written exam (60min??)

Anwesenheitspflicht 90%
Projektdokumentation

Im Rahmen der Masterthesis sollen die erworbenen Fach- und Methodenkenntnisse von den Studierenden eingesetzt werden. Ein wichtiger Fokus liegt auf der korrekten Anwendung der Techniken des wissenschaftlichen Arbeitens. Die Studierenden werden bei der Vorbereitung der Thesis durch erfahrenes wissenschaftliches Personal unterstützt. Es kann in Abstimmung mit dem Studiengangmanagement zu Beginn des letzten Semesters der Vertiefungsmodule mit der Bearbeitung begonnen werden.

Ziel der Lehrveranstaltung ist es, den Studierenden die grundlegenden Kenntnisse des österreichischen, schweizeri-schen, deutschen, europäischen und internationalen Stiftungsrechts zu vermitteln.

Die Lehrveranstaltung behandelt folgende Themenfelder:

• Grundlegende Kenntnisse im österreichischen Stiftungsrecht
• Kenntnis der Gemeinsamkeiten und Unterschiede zwischen den österreichischen und liechtensteinischen Gestaltungsoptionen im Stiftungsrecht
• Anwendbarkeit des österreichischen Stiftungsrechts
• Grundkenntnisse im schweizerischen Stiftungsrecht
• Anwendbarkeit des schweizerischen Stiftungsrechts
• Grundlagenwissen auf dem Gebiet der gemeinnützigen Stiftungen in der Schweiz mit besonderem Au-genmerk auf den Swiss Code of Best Practice
• Grundkenntnisse im deutschen Stiftungsrecht

Interaktive Vorlesungen, ergänzt durch Case Studies aus der Praxis; eingehende Diskussion unter Einbeziehung der Studierenden.

Zu Beginn des dritten Moduls werden den Studierenden die grundlegenden Kenntnisse des Stiftungsrechts der be-nachbarten Rechtsordnungen Österreich, Schweiz und Deutschland vermittelt. Die Studierenden lernen die Rechts-formen der österreichischen Privatstiftung, der schweizerischen Stiftung und der deutschen Stiftung sowie deren Aus-prägungen und Gestaltungsmöglichkeiten eingehend kennen. Eröffnet wird ein Einblick in die grundlegenden Struktur- und Wesensmerkmale der jeweiligen Stiftung ebenso wie in die Besonderheiten der einzelnen Rechtsordnungen. Aufbauend auf diesen erworbenen Kenntnissen werden Verknüpfungen zum liechtensteinischen Stiftungsrecht (Mo-dul 2) hergestellt und rechtsvergleichende Überlegungen angestellt. Aufgrund der Nahebeziehung zwischen dem ös-terreichischen und liechtensteinischen Stiftungsrecht – bedingt durch die gegenseitige Rezeption in der Vergangenheit – wird der Schwerpunkt in diesem Bereich auf die Gemeinsamkeiten und Unterschiede bei den Gestaltungsmöglichkei-ten der beiden Stiftungsrechte gelegt. Um das erlernte Wissen zu den einzelnen Stiftungsrechtsordnungen zu vertie-fen, finden im Anschluss an die Vorlesungen jeweils Case Studies statt, in denen die Studierenden anhand praktischer Fälle lernen, das neue Wissen entsprechend anzuwenden. Zum Abschluss erfolgt eine Einführung in das Recht der gemeinnützigen Stiftungen in der Schweiz, welches mit der Schaffung des rechtlich unverbindlichen Swiss Foundation Code in diesem Bereich eine Vorreiterrolle eingenommen hat. Neben allgemeinen Informationen über das gemeinnüt-zige Stiftungsrecht wird besonderes Augenmerk auf die Entwicklung und Ausgestaltung des Swiss Foundation Code sowie die praktischen Erfahrungen mit diesem Regelwerk gelegt. Daneben erfolgt eine grundlegende Einführung in das deutsche Stiftungsrecht. Abgerundet wird das Modul durch die Analyse und Bearbeitung praktischer Fälle.

In their Master’s Thesis, students use scientific methods and work in accordance with standards of scientific writing. The master's thesis is typically related to one of the four subject areas that constitute the core of the curriculum (i.e., Business Process Management, Data and Application Security, Data Science, and Digital Innovation).

• The thesis is assessed by a faculty member from the Institute of Information Systems (professor, assistant professor, visiting professor or senior lecturer).The thesis is presented and defended in an oral examination. The examination committee is composed of the Academic Director, another faculty member, and an external expert appointed by the Vice-Rector for Teaching.The time for producing the completed thesis is defined on the thesis proposal (“exposé”) and may not exceed 22 weeks.

• After successful submission of the master's thesis, students will have demonstrated their ability to plan, execute and manage research projects autonomously.

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles).
• Oates, B.J. (2006). Researching Information Systems and Computing. London, UK: Sage Publications.
• Recker, J. (2012). Scientific Research in Information Systems: A Beginner’s Guide. Heidelberg, Germany: Springer.

• Exposé: The seminar paper that is developed in the Research Seminar module serves as an exposé for the master’s thesis if the student has passed the Research Seminar module and if the student has not submitted another exposé signed by the supervisor to the study administration (master.information-systems@uni.li) by 01 February (summer semester) or 01 July (winter semester).Regulations and forms: Students must adhere to the Guidelines for Writing Academic Papers in Economics and are asked to use the university’s official Template for writing their master’s theses. In addition, students must carefully review the Study and Assessment Regulations and Master Thesis Assessment Criteria. All documents are available on the university’s intranet (“Regulations and Forms”).Submission: The completed master’s thesis must be submitted to the central service desk by 30 June (summer semester) or 30 November (winter semester). (Students should check the opening times of the central service desk, especially during the summer months.) If either of these dates falls on a weekend or a public holiday, the deadline is automatically extended to the next workday. The submission must include: (1) two signed copies in adhesive binding and (2) two signed copies in spiral binding. In addition, students must upload their completed theses as pdf documents to Moodle.Presentation and defence: The master’s thesis must have been evaluated with a grade of 3.8 or higher to attend the Presentation and Defence course. A detailed schedule will be announced via Moodle and/or via e-mail. Students have 12-15 minutes to present their theses, another 15 minutes is for discussion. Apart from subject knowledge, grading criteria are presentation structure (information flow, line of argument etc.), design (formatting, figures, animations etc.), mechanics (grammar, typos, c itation etc.), appearance (eye contact, gestures etc.), and elocution (language, clarity, rhetoric etc.).

Management Information Systems focuses on large-scale application software packages that support end-to-end processes, information and document flow, reporting, and data analytics in organizational settings. The course covers eight primary topics:

• Enterprise applications
• E-business
• Managing knowledge
• Enhancing decision-making
• Building management information systems (MIS)
• Managing projects and global systems
• MIS-related integration, transformation, innovation, and change
• Case studies on current MIS topics

• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.Case studies are used to discuss the course contents and to train students in using the methods covered.

After successful completion of the course, students will:

• understand the fundamental concepts and definitions in the area of enterprise systems and know application systems like ERP, CRM, and SCM systems
• understand the role of management information systems in achieving sustainable competitive advantage and integrating processes along the value chain
• be able to assess the applicability of software solutions in various business scenarios using comprehensive evaluation schemes
• be able to identify the business problems that typically emerge in enterprise systems design and use

• Compulsory reading:Papers and case-study material are provided.

Written exam (90min)