Process Mining provides a comprehensive exploration of the fundamentals of process mining, including conceptual foundations, methods, and technologies used for analyzing business processes with the help of digital trace data recorded in event logs.
Students attending this course will gain knowledge of foundational concepts and algorithms in process mining and acquire practical skills to mine digital trace data using process mining techniques and software. Students will also learn the main steps of conducting a process mining project within an organization as well as common challenges and strategies of process mining analysis.

The course covers four primary topics:

• Petri-net foundations of process analysis
• Process mining algorithms, including process discovery and conformance-checking algorithms
• Process mining project methodologies, strategies, and challenges of process mining analysis
• Process mining tools and applications

• The course involves interactive lectures with exercises and practical sessions with process mining software that allow integrating theoretical knowledge with analytical skills. The practical exercises run in class will allow students to work with process mining hands-on and prepare for the final exam.

After successful completion of the course, students will

Professional competence

• understand how a process mining project can be conducted in practice
• be aware of best practice strategies for conducting process mining analysis
• know how to analyze digital trace data using process mining tools

Methodological competence

• understand the foundational concepts of process mining
• understand how process mining algorithms work
• run process discovery and conformance-checking algorithms

Social competence

• know about the pitfalls of process mining
• understand how process mining is embedded in an enterprise setting

Personal competence

• be able to identify business challenges for which process mining is a fitting solution
• be able to identify challenges of process mining analysis
• be able to apply a process-oriented way of thinking when approaching data science projects

Technological competence

• understand and explain the foundational concepts of process mining
• understand and explain how process mining algorithms work
• be able to use popular process mining tools

• van der Aalst, W. M., & Carmona, J. (2022). Process Mining Handbook. Springer Nature.
• Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. (2018). Fundamentals of Business Process Management (2nd edition). Berlin, Germany: Springer.
• Pointers to additional readings will be provided during the lectures.

Written exam

This optional module allows for various kinds of research studies. It is closely connected to the five units of the Liechtenstein School of Architecture and is usually part of ongoing research projects. The supervision consists of directing the students towards clear results within a given field of research. The individual study is reviewed within the respective unit.

Sustainable Design Unit:
Research in Sustainable Architecture - Focus on Fluidglass This elective module invites participants to explore the transformative potential of Fluidglass technology within the realm of sustainable architecture. In alignment with the ongoing research at the LSA, this module allows you to examine how innovative facade technologies such as Fluidglass can influence the future of construction. Participants will have a unique opportunity to contribute to the advancement of Fluidglass in the context of sustainability and contemporary building practices. Depending on the desired credit allocation, tailored work packages will be developed. These may include an exploration of current advancements in facade technology, competitor and market analyses, or technical and cost simulations. Your interests and prior knowledge will be taken into account during the initial phase of the project. Participants will engage in self-directed research, working either individually or in collaborative groups. The scope of your work will be customized to meet the specific requirements of your selected work packages and will be guided by the research unit. While there are no formal prerequisites for this module, it is advisable to undertake it in the third semester to build upon foundational knowledge. Essential literature and resources will be provided at the commencement of the course, with regular updates throughout the semester to support your work and great importance is placed on equipping the participants with a strong foundation for future projects and scientific work in the field of sustainability.

Self-defined design or research studies, developed individually or in groups agreed upon with research units and under the guidance of mentors. The size of the module is determined by the respective unit.

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

Relevant reading will be made available at the beginning of the course. A list of recommended literature will be announced in the course and updated on an ongoing basis.

Minimum 75% compulsory attendance, regular meetings with instructors, continuous assessment, portfolio and final review.
The final grade is calculated according to the weighting of the following components: final submission (80%) and oral presentation (20%).

Individual appointments will be set with the tutor.

Ein praktischer Einstieg in Podcasts, Videoproduktion und Webradio. Studierende entwickeln eigenständig Formate - von der Idee bis zur Veröffentlichung auf Spotify, Apple Podcasts, YouTube und dem Uni-Webradio.

Broadcasts, Podcasts, Audio- und Videoformate, Redaktion, Präsentationen, Gruppen- und Projektarbeit

• Eigenständige Produktion journalistischer Audio- und Multimediaformate
• Produktion von Podcasts, Interviews und Radiosendungen
• Verständnis aktueller Trends in Audio- und Onlineproduktion
• Reflexion zur Stimme und Wirkung in sozialen Medien
• Aktive Mitwirkung am Aufbau des Campus Radios der Universität

Smartphone, Mikrofon, Laptop, Audio-Software (z.?B. Audacity)

Benotung

• 40% Präsentation (mind. 5 Seiten)
• 60% Eigenständig produziertes Audioformat (Deutsch oder Englisch)

mindestens 80% Anwesenheitspflicht

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.

Projects will address various aspects of business process management and digital transformation. Exemplary topics include but are not limited to process elicitation and understanding, analysis of process related data, digital business models, change management, human-system interaction. Projects are expected to deliver conceptual designs or to carry out practical case studies on various aspects of digital business.

• 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.

After successful completion of the course, students will

Professional competence

• be able to analyse real-world cases
• integrate knowledge to identify areas of improvement or innovation
• use appropriate methods to develop recommendations for a case company

Methodological competence

• manage a (small) project
• identify and structure existing information
• work with domain experts (external partners)

Social competence

• self-organise within a group
• work in a group and with external partners
• handling criticism and demonstrate the ability to criticise in a constructive manner

Personal competence

• reflect on limitations of their own work
• work on tasks independently within a group
• manage time

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles).

Seminar paper (50%), presentations (50%); attendance is mandatory (80%)

This optional module allows for various kinds of research studies. It is closely connected to the five units of the Liechtenstein School of Architecture and is usually part of ongoing research projects. The supervision consists of directing the students towards clear results within a given field of research. The individual study is reviewed within the respective unit.

Built Heritage & Upcycling Unit:
Modern architecture came to Liechtenstein in 1924: on a bicycle in the form of the young German architect Ernst Sommerlad. Sommerlad reinterpreted international modernism for the Alpine region and created dozens of residential buildings in the Principality as well as in Appenzell, St. Gallen, Graubünden and Vorarlberg. On the occasion of a scientific symposium at the University of Liechtenstein in fall 2025, we are taking a close scientific look at Sommerlad' s broad and exciting oeuvre in cooperation with the state and the OST (Eastern Switzerland University of Applied Sciences). Be part of it!

Self-defined design or research studies, developed individually or in groups agreed upon with research units and under the guidance of mentors. The size of the module is determined by the respective unit.

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

Relevant reading will be made available at the beginning of the course. A list of recommended literature will be announced in the course and updated on an ongoing basis.

Minimum 75% compulsory attendance, regular meetings with instructors, continuous assessment, portfolio and final review.
The final grade is calculated according to the weighting of the following components: final submission (80%) and oral presentation (20%).

Individual appointments will be set with the tutor.

Group projects are also possible, as well as group work with individual submissions.

Im Zentrum steht eine ganzheitliche Betrachtung von Gebäuden, in der alle Bauteile ihre Funktionen erfüllen und im interdisziplinären Zusammenspiel den gewünschten architektonischen Ausdruck definieren und auszudrücken vermögen. Arbeitsabläufe, Arbeitsweisen, Techniken, disziplinare Vernetzungen, planerische Abhängigkeiten und rechtliche Rahmenbedingungen sollen vermittelt und Optimierungspotential diskutiert werden. In Gesprächen mit Fachdozierenden aus den Bereichen Baukonstruktion, Statik, Bauphysik, Haustechnik und Baukostenmanagement werden die eigenständig entwickelten Erklärungen zur Wirkung und Tauglichkeit der Konstruktionen dargestellt und diskutiert. Die Gewichtung der Betrachtung und Analyse liegt beim Bauen im Bestand und dessen nachhaltigem Erhalt sowie der Adaptierung nach geltenden Standards der Bau- und Gebäudetechnik.

siehe nachfolgende Lehrveranstaltungen

Die Lernergebnisse und zu erwerbenden Kompetenzen dieses Moduls ergeben sich aus den nachfolgend beschriebenen Lehrveranstaltungen.

Die Abschlussnote wird errechnet aus den Noten der beiden Lehrveranstaltungen mit einer Gewichtung von jeweils 50%. Ein erfolgreicher Abschluss setzt zudem voraus, dass in beiden Lehrveranstaltungen jeweils mindestens die Note 4.0 erreicht wurde. Modalität siehe Lehrveranstaltung.

Business Statistics covers statistical methods that are used to support decision-making in business contexts, so it also provides a methodological foundation for the students’ master’s thesis projects. The course builds on the basic concepts of statistical testing and estimation theory that are usually taught in bachelor’s programmes. The course covers five primary topics:

• Graphic and numeric characterisations of random variables and their distributions
• Framework and basic applications for testing hypotheses and estimating parameters
• The ordinary least squares (OLS) method
• Simple linear regression, including parameter estimation, diagnostic plots, hypothesis testing, predictions, and model specifications using log-transformations

• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
• Students complete homework assignments after each lecture.

After successful completion of the course, students will

Professional competence

• know the difference between descriptive statistics and statistical inference based on stochastic models
• understand the framework of testing hypotheses and estimating parameters
• know the assumptions made in basic testing and estimating procedures when drawing general conclusions
• be able to explain the classic linear model assumptions

Methodological competence

• be able to describe the distributions of random variables and to calculate and interpret their moments
• be able to derive the minimum sample size for basic testing and estimation procedures
• be able to apply the ordinary least squares method to derive estimators and compare their statistical properties
• run simple linear regressions and interpret the results correctly

Social competence

• be able to organise learning materials and work in groups
• be able to discuss statistical tasks with their colleagues on a sound mathematic level

Personal competence

• be able to “think statistically” i.e., they can interpret statistical assertions in their job as well as everyday life correctly

Technological competence

• be familiar with statistics programming

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles).
• Berensen, M.L., Levine, D., & Szabat, K.A. (2014). Basic Business Statistics (13th edition). Essex: Pearson Education Limited.

Written exam

In the viva voce examination the doctoral student proves that he/she meets the requirements on the dissertation by publically defending his/her dissertation.

The Chairperson of the Board of Examiners, the supervisor and the co-supervisor(s) shall determine a grade for the viva voce examination.

In this seminar, key topics of high relevance to contemporary urban design are discussed. These are approached in a transdisciplinary manner and embedded in a holistic view. Based on the principles of decarbonisation, adaptation to climate change, the fostering of biodiversity and an inclusive and equitable distribution of space, urban
design is understood as a key to the spatial discourse. Over the course of the semester, students will engage intensively with a selected topic and develop their own position on it using theoretical texts and case studies from practice.

Seminar with input lectures and active participation of the students in group discussions, assignments etc.

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

Relevant reading will be made available at the beginning of the course. A list of recommended literature will be announced in the course and updated on an ongoing basis.

Minimum 75% compulsory attendance and continuous assessment.
The final grade is calculated according to the weighting of the following components: final submission (80%) and oral presentation (20%).

This course is provided through Coursera and is offered by the Imperial College London.

This Creative Thinking specialisation consists of three courses, designed to enhance learners' creativity skills by employing diverse brainstorming techniques, systematic creativity tools, and advanced creative thinking strategies. Throughout the specialisation, participants will gain expertise in using approaches such as the creativity diamond framework, biomimicry, analogy, metaphor, and AI-enabled platforms in order to generate innovative ideas and effectively address challenges or opportunities in their projects or activities.

Creative Thinking Tools for Success and Leadership

Applied Learning Project

Throughout the three courses within this specialisation, you will have the opportunity to undertake a series of assessments where you will apply what you have learned about different aspects of creative thinking, at an Introductory, Systematic, and Advanced level.

Instructor: Peter Childs (Head of the Dyson School of Design Engineering at Imperial College London)

This FU consists of 3 courses:

Course 1: Introduction to Creative Thinking: Tools for Success
Course 2: Systematic Creative Thinking: Tools for Success
Course 3: Advanced Creative Thinking and AI: Tools for Success

The course starts on 10th of February 2025.
The course must be completed by 23rd of May 2025.

All parts of this course are free of charge.

Online courses

• Problem Solving
• Creativity
• Brainstorming
• Innovation
• Creativity Diamond

see the course descriptions

Attenance min. 80% mandatory

Grading