Practise communicative and cultural skills and competences in German on level A2 (cf. CEFR descriptors).

This is a suggested schedule but, if practicable, changes can be made in accordance with the wishes of the participants.

Information about the placement test is provided on the website of the cross-faculty elective subjects > language courses and by the International Office

Interactive teaching

Develop German language competence on level A2 (cf. CEFR descriptors), develop cultural competence

• listen to, understand, and react to simple texts and dialogues
• read and understand simple texts and dialogues
• know and use basic grammar and vocabulary
• write simple texts
• use learning strategies successfully
• develop cultural competence

Develop German language competence on level A2 (cf. CEFR descriptors), develop cultural competence

• listen to, understand, and react to simple texts and dialogues
• read and understand simple texts and dialogues
• know and use basic grammar and vocabulary
• write simple texts
• use learning strategies successfully
• develop cultural competence

Available on Moodle

Parts of assessment
A: written/oral assessment during the semester
B: oral test

Attendance: minimum 80% required

Grading

After successful completion of the seminar, a language certificate (University of Liechtenstein) may be offered. It is based on the performance record of the standardized language placement test onSET.

cross-faculty course:
Rules for registration: www.uni.li/cross-faculty

Advanced Machine Learning covers several advanced topics in the field of machine learning and is concerned with requirements engineering in particular. Students learn to analyse certain types and large amounts of data. The course has three parts: Managing and Conducting Data-driven Projects, Machine Learning (ML) Techniques and Applications, and Large Scale Machine Learning. In more detail, the topics covered are:

• Requirements engineering for machine learning and business intelligence projects
• ML in Production - from models to products that are monitored and updated
• Advanced ML topics, e.g., AutoML, Time series analysis
• Distributed and parallel computing for machine learning and data processing with a focus on Spark

• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.

After successful completion of the course, students will

Professional competence

• have deepened their understanding of the field of machine learning and acquired a large set of machine-learning techniques
• understand the challenges and solutions of processing large amounts of data
• gather requirements for projects in the field of machine learning

Methodological competence

• be able to apply a diverse set of methods to address a number of machine learning problems

Personal competence

• critically reflect on analytical outcomes
• improve and mitigate self-inflicted errors

Technological competence

• use Python libraries for automated machine learning such as hyperopt, time series analysis
• understand large scale data processing frameworks such as Spark

Written exam (60min)

The Professional Practice gives students the opportunity to work in an architectural office or related fields to gain new practical experience in different stages from design studies, competition entries and construction projects up to the on-site building process. The Professional Practice is planned and set up by the students, under the guidance of mentors. Thereby students learn to apply for a new job. They prepare a professional portfolio and document their learnings during the professional practice. Those who already work in an architecture office or in related fields can also complete the Professional Practice module but must arrange a work situation that allows them to gain experience in a new field within their employment for the required duration. The experiences and insights gained during the Professional Practice are presented at the University of Liechtenstein and reviewed in front of the mentors.

Professional practice under the guidance of mentors.
Professional Practice enables students to establish a close link to practice. By working on studies, competitions or real
projects, students gain a deeper insight into various areas and phases of architecture and related fields. By collaborating
on real projects, students are enabled to supplement their theoretical studies with practical work.

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

Minimum 75% compulsory attendance
Two mentoring meetings, the first before starting the professional practice and the second during the professional practice.
The final grade is calculated according to the weighting of the following components: professional practice documentation (60%) and presentation (40%).

The Master's Thesis is carried out by the student as part of an Advanced Studio and is supervised by the unit. The thesis contains a developed hypothesis that is verified (or falsified) as part of the design project. In addition to the actual design project, the Master's thesis includes the design and production of the thesis book. This consists of
three parts: the documentation of the design project, a theoretical report and a technical report. The formal aspects of the thesis and the thesis book are described in the Master's thesis regulations.

Mentored project work in the design studio.

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

Successful completion of 3 Advanced Studios in the Master´s degree programme.

Minimum 75% compulsory attendance, continuous assessment, midterm and final reviews.
The final grade is calculated according to the weighting of the following components: design project (60%), final presentation (10%) and thesis book (30%: 10% theoretical report, 10% technical report and 10% project documentation).

• Data Management covers the modern data-management cycle, from the collection of data from diverse sources to the preparation of data for data-driven applications. Students learn how to handle various data formats, how to assess and improve data quality, and how to store and process data using SQL, NoSQL, and Hadoop technologies. The course covers eight primary topics:Modern data-management requirementsDatabase system architectureDiagnosing and handling data quality problemsRelational databases (SQL)Hands-on labs with MySQLConcurrency control techniquesNoSQL databases (e.g., MongoDB)Apache Hadoop (HDFS, MapReduce)

• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.

After successful completion of the course, students will

Professional competence

• understand the basic concepts of modern data management
• have gained insights in advanced concepts of modern data management

Methodological competence

• be able to apply the data management stack from conceptual database design to data query and manipulation
• be able to collect and prepare data for data-driven applications

Social competence

• be able to organise learning materials and work in groups
• be able to divide problems into meaningfully tasks, work on them and help each other within the group

Personal competence

• be able to apply the learned theoretical content to real-world scenarios
• have an increased capability of structural thinking

Technological competence

• be familiar with SQL, in particular with MariaDB/MySQL
• be familiar with MongoDB

Written exam (60min)

Das sechste Modul ist als Wahlmodul ausgestaltet. Entweder erfolgt die Teilnahme am Modul sechs oder die Studierenden belegen ein frei wählbares Modul der anderen Executive Masterstudiengänge in International Taxation, Bank- und Finanzmarktrecht oder Wirtschaftsstrafrecht. Ebenfalls besteht die Möglichkeit, eine schriftliche Case Study im Rahmen des „I&F Family Wealth Preservation Award“ zu bearbeiten.

Ziel der Lehrveranstaltung ist es, den Studierenden das europäische und internationale Gesellschaftsrecht mit FL-Bezug sowie die Grundlagen der Compliance näherzubringen.
Die Lehrveranstaltung behandelt folgende Themenfelder:

• Grundlegende Kenntnisse auf dem Gebiet des europäischen Gesellschaftsrechts im Kontext der liechten-steinischen Rechtsordnung
• Grundwissen im europäischen Recht der Spaltung, Fusion und Umwandlung von Gesellschaften mit Ver-weis auf entsprechende nationale Regelungen des liechtensteinischen Rechts
• Grundkenntnisse im internationalen Gesellschaftsrecht unter Einbezug der Auswirkungen auf Liechten-stein
• Grundlagenwissen sowohl auf dem Gebiet der justiziellen Zusammenarbeit in Strafsachen als auch in Zi-vilsachen
• Grundlegende Kenntnisse im UK-Gesellschaftsrecht

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

Das sechste Modul beschäftigt sich mit den internationalen gesellschaftsrechtlichen Regelungen im liechtensteinischen Umfeld. Zu Beginn wird den Studierenden ein Einblick in das UK-Gesellschaftsrecht gewährt. Dabei lernen sie die grundlegenden Unterschiede zwischen dem Common Law und dem Civil Law kennen. Weitere Schwerpunkte dieses Moduls stellen die polizeiliche und justizielle Zusammenarbeit in Zivil- und Strafsachen sowie das Sorgfaltspflichten-recht dar. Insofern lernen die Studierenden die charakteristischen Merkmale und Voraussetzungen auf diesen Gebieten kennen und erhalten einen Überblick über die jeweiligen Verfahrensabläufe. In diesem Zusammenhang werden den Studierenden auch die Besonderheiten der Geldwäschereibekämpfung nähergebracht und ein Einblick in die Abläufe der Verfahrensarten bei der Bekämpfung von Geldwäsche gewährt.
Daran anschliessend lernen die Studierenden die nationalen, europarechtlichen und völkerrechtlichen Rechtsquellen zu den einzelnen Themenbereichen des internationalen Gesellschaftsrechts kennen.
Hierzu werden zunächst die zentralen Aspekte des europäischen Gesellschaftsrechts im Zusammenspiel mit dem nationalen Gesellschaftsrecht eingehend erläutert sowie die supranationalen Rechtsformen dargestellt. Im Anschluss daran wird das internationale Gesellschaftsrecht Liechtensteins ausführlich besprochen und diskutiert. Dabei wird insbesondere die zentrale Bedeutung des Gesellschaftsstatuts als Anknüpfungselement erläutert sowie die Sitzverlegung von Gesellschaften eingehend thematisiert.

Schriftliche Prüfung à 90 Min.; hierin werden sämtliche Gebiete der angegebenen einzelnen Lehrveranstaltungen abgedeckt

Alternativ kann ein frei wählbares Modul der anderen angebotenen Executive Masterstudiengänge (z.B. in International Taxation oder in Bank- und Finanzmarktrecht) abgeschlossen werden. Ebenfalls besteht die Möglichkeit einer schriftlichen, wissenschaftlich ausgearbeiteten Case Study im Rahmen des „I&F Family Wealth Preservation Award“ zu bearbei-ten. Insgesamt können nur zwei der drei Wahlmodule ersetzt werden. Mindestens eines dieser Wahlmodule (Modul 5 bis 7) muss als Vorlesungsmodul besucht werden.

Das Modul vermittelt die gesellschaftsbezogenen Aspekte der Architektur, von ethischen Herausforderungen der modernen Architektur bis hin zu Prozessen der Urbanisierung. Es bietet Einblicke in das Verhalten von Akteuren und die Entwicklung von Perspektiven verschiedener Gesellschaften, die die Raumproduktion beeinflussen. Nach Abschluss des Moduls sollen die Studierenden fähig sein, das eigene Schaffen in mehreren gesellschaftlichen Kontexten kritisch zu
reflektieren sowie den ethischen, kulturellen und politischen Wert von Architektur im digitalen Zeitalter erkennen können.

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.

The Built Heritage seminar poses the question of architectural heritage, values and valences as well as long-lasting processes, typologies and buildings against a global horizon. In times of resource scarcity and climate change, the already built space is playing an increasingly central role in planning. This raises the significance of the history of architecture. Knowledge of the built heritage and its conditions is becoming more important for architects than ever. The networking of the world, its exchange and cultural transfer have inspired architecture for centuries. A focus purely on European architectural history no longer seems appropriate in view of our globalised economy and the often globally socialised and working young generation of architects, facing global problems. A special emphasis of the seminar will be on the many forms of worldwide architecture with a low carbon footprint, using natural and local materials while creating a strong identity. The aim of the seminar is to broaden the classical frame of reference both temporally and, above all, spatially and to analyse connections, longevity, and differences.

Seminar with provision of specialised literature and lecture inputs.

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

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%).

Business Process Analysis focuses on process analysis, covering approaches and methods for designing, analysing, and simulating processes in organisations. The course covers four primary topics:

• Introduction to process analysis
• Process modelling and design
• Process flow analysis
• Process simulation

• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.

After successful completion of the course, students will

Professional competence

• know basic methods of process modelling for analysing, designing, and implementing information systems in organisations
• be able to use qualitative and quantitative methods of process analysis to design, and improve business processes in organisations

Methodological competence

• be able to complete and manage process selection, design, and analysis projects
• be able to perform simulations on business process data

Personal competence

• be able to manage learning progress independently
• be able to make prioritization decisions under uncertainty

Technological competence

• be able to apply international standards for business process design and analysis

Written exam

AI-based design tools are fundamentally changing how designers work across various industries. AI-based design tools make independent design decisions and, in some cases, execute entire design processes. They employ technologies typically associated with artificial intelligence, including machine learning, pattern recognition, meta-heuristics, and evolutionary algorithms.
AI-based design tools enable the generation of a diverse range of design artifacts, including next-generation computer chips, specialized software for specific domains, three-dimensional virtual worlds, and extensive content, such as for video games and feature films. The applications for such AI-based design tools are also expanding to other industries, such as mechanical engineering, aerospace, and architecture.

Instead of creating artifacts by directly manipulating their representations, designers select tools, decide on design parameters, set values for these parameters, and evaluate and learn from the analysis of the results the tools produce. Design work in such situations involves intense interaction with AI-based tools. Designers need to be mindful of the logic, capabilities, and limitations of the tools and the algorithms these tools employ and find ways to make sense of and deal with the often unanticipated outputs of such tools.

The course addresses this increasingly important role of AI-based design tools by

• discussing the conceptual foundations of AI-based design tools.
• discussing how AI-based design tools change the nature of work and the role of human designers.
• analysing examples of using AI-based tools in design practice.
• providing hands-on experience in agent-based modelling for students to simulate the behavior of these tools.
• providing hands-on experience in using AI-based design tools for the design of virtual worlds.

• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical de-sign and analysis skills.
• Contemporary scientific publications from Information Systems, Management, and Computer Science are dis-cussed in class.
• The NetLogo software is used to model and simulate AI-based design agents.
• Further software tools may be used throughout class

After successful completion of the course, students will

Professional competence

• understand the main concepts, theories, and methods related to AI-based design tools
• understand the applications for AI-based design tools in different industries

Methodological competence

• be able to apply central concepts and methods to relevant areas of application
• be able to identify areas of improvement using new technologies
• be able to analyse examples and provide recommendations in design practice

Social competence

• be able to reflect their own experiences in the field of AI-based design tools concerning the presented topics
• be able to work in groups and deal with cases from practice in order to identify and discuss challenges and so-lutions

Personal competence

• be able to analyse how AI-based design tools change work processes
• possess knowledge to identify areas of improvement or innovation
• be able to apply their knowledge in real-life cases

Technological competence

• be able to develop agent-based models for simulating AI-based design tools

Written exam