Master

Multilingual Technologies

Multilingual Technologies

part-time

Multilingual Technologies combines language and IT. This Master's degree program, which is unique in Austria, is offered in cooperation with the Center for Translation Studies at the University of Vienna and is aimed at all those who already have a Bachelor's degree in engineering or translation science and are interested in language technologies as well as multilingual solutions and concepts. The interdisciplinary character of the degree program qualifies students for future-oriented professional fields, for example in language technology or in the field of machine translation.

Department
Engineering
Topic
Technologies

Highlights

  • Interdisciplinary character

  • Future-oriented professional field

  • Master's degree program unique in Austria

     

    Facts

    Final degree

    Master of Science

    Duration of course
    4 Semesters
    Organisational form
    part-time

    tuition fee pro semester

    € 363,361

    + ÖH premium + contribution2

    ECTS
    120 ECTS
    Language of instruction
    English

    Application winter semester 2023/24

    1st October 2022 to 13th June 2023

    Study places

    30

    1 Tuition fees for students from third countries € 727,- per semester

    2 for additional study expenses (currently up to € 83,- depending on degree program and year)

    Before the studies

    You already have a Bachelor’s degree in engineering or in translation studies and are interested in language technologies as well as multilingual solutions and concepts. With this joint Master’s degree of FH Campus Wien and the Centre for Translation Studies at the University of Vienna, you can combine your knowledge of language and IT in a future-oriented education and training profile.

    Why you should study with us

    Participate in interdisciplinary student or research projects

    This way, fun and experience are guaranteed!

    Practical training on campus

    Modern laboratory equipment and high-tech research facilities enable practice-oriented teaching.

    Unique job opportunities


    Obtain additional certificates while still studying and increase your market value.

    Admission to the Master's degree program Multilingual Technologies requires a Bachelor's degree in a relevant subject (e.g. Computer Science and Digital Communications of FH Campus Wien or Transcultural Communication of the University of Vienna) as well as the following subject-specific knowledge:

    • a. Basic knowledge of language technologies and technical communication
    • b. Basics of computer science, basic methods and tools of software engineering

    Knowledge listed under a) is fulfilled by the Bachelor's degree program Transcultural Communication or the completion of the extension curriculum Language Technologies and Technical Communication at the Center for Translation Studies. Knowledge listed under b) is fulfilled by the Bachelor's degree program Computer Science and Digital Communications or the completion of the  extension curriculum Computer Science  (for students of the University of Vienna) at FH Campus Wien.

    Regulation for the admission of third country citizens (PDF 233 KB)

    Information for applicants with non-Austrian (school) certificates (PDF 145 KB)

    Your application is submitted via the online application form.

    You will need the following documents for your online application:

    •     Birth certificate
    •     Proof of citizenship/passport
    •     University degree (certificate of bachelor or diploma degree / equivalent foreign certificate)
    •     Transcript of Records
    •     Proof of extension curriculum
    •     Letter of motivation in English
    •     Proof of English language proficiency (minimum level B2)
    •     Short curriculum vitae
    •     Translation of foreign language documents

    Please note:
    It is not possible to save incomplete online applications. You must complete your application in one session. Your application will be valid as soon as you upload all of the required documents and certificates. In the event that some documents (e.g. references) are not available at the time you apply, you may submit these later via e-mail, mail or in person by no later than the start of the degree program.

    Admission procedure: the admission procedure includes an interview with members of the admission committee (representatives of the University of Vienna and FH Campus Wien). This interview will take place online until further notice. You will receive the date for the admission procedure from the secretary's office.

    • Objective
      It is our objective to offer a study place to those persons who complete the admission procedure with the best results. The test procedures are oriented towards the skills required for the intended profession.
    • Procedure
      In the interview, you will answer some basic subject-specific questions, some questions about yourself, and explain your motivation for choosing the program (duration: approx. 30 minutes). If you have not yet reached the required entry level for the degree program, you will receive recommendations after admission on how best to prepare yourself in a subject-specific way.
    • Criteria
      The admission criteria are based on performance only. You will receive points for the oral interview, which will determine the ranking of the candidates. Geographical assignments of the applicants have no influence on the admission. The admission requirements must be met. The entire process as well as all test results and evaluations of the admission procedure are documented and archived in a comprehensible manner.

    During the studies

    This Master's degree program, which is unique in Austria and also innovative by international standards, focuses on language technologies, methods for their generation and use, and on language resources. It has a strong interdisciplinary character due to the combination of translational, transcultural, computer science and linguistic disciplines. 

    The joint Master's degree program will be based in the Department Engineering of FH Campus Wien and the Center for Translation Studies of the University of Vienna. It thus combines the special profile elements, professional strengths and scientific expertise of both institutions to create a future-oriented interdisciplinary education and training profile.

    Curriculum

    Introduction to Computational Linguistics ILV
    3 SWS
    6 ECTS

    Introduction to Computational Linguistics ILV

    3 SWS   6 ECTS

    Lecture contents

    - Introduction to the concepts and directions of traditional linguistics
    - Classical tasks of computational linguistics
    - Presentation of different methods for language processing from tokenization to sentiment analysis
    - Different NLP systems and computational linguistic analysis models
    - Discussion of the current state of research and further research ideas
    - Practical introduction to basic methods of automatic language processing

    Assessment methods

    Continuous assessment
    Written final examination, ongoing delivery of implementations, presentations.

    Teaching methods

    Lecture, practical exercises, presentations, discussions, feedback.

    Language

    English

    Introduction to Machine Learning for Language Processing ILV
    3 SWS
    6 ECTS

    Introduction to Machine Learning for Language Processing ILV

    Lector: Liad Magen

    3 SWS   6 ECTS

    Lecture contents

    - ML definition, application areas and classification of ML algorithms (Supervised, Unsupervised, Reinforcement Learning)
    - Classical ML algorithms: kNN, Decision Trees, Naïve Bayes, NN, SVM, Ensamble Learning and Random Forest
    - Typical approach to ML projects: Define requirements, collect, filter and represent data, define and extract features, deploy algorithms and evaluate their performance, improve iterative ML pipeline.
    - Introduction to Deep Learning: CNN, RNN, Generative Networks

    Assessment methods

    Continuous assessment
    Participation in discussions, elaboration of exercise examples, own ML-project, written exam

    Teaching methods

    Theory transfer in class, discussion of practical examples, own ML-project

    Language

    English

    Multilingual and Crosslingual Methods and Language Resources VO
    2 SWS
    4 ECTS

    Multilingual and Crosslingual Methods and Language Resources VO

    2 SWS   4 ECTS

    Lecture contents

    - Different types of language resources (terminology, lexicon, controlled vocabulary, thesaurus etc.).
    - Methods for representing, creating, disseminating and using multilingual language resources, including the Linguistic Linked Open Data (LLOD) approach and linguistic Data Science in general.
    - Multilingual and cross-lingual methods for improving communication using language resources and computational linguistic approaches.
    - Practical examples from the field of LLOD

    Assessment methods

    Final exam
    Final Written Exam.

    Teaching methods

    Lecture/lecture, discussion, case solutions.

    Language

    English

    Programming and Algorithms for Language Technologies VO
    1 SWS
    2 ECTS

    Programming and Algorithms for Language Technologies VO

    Lector: Dipl.-Ing. Georg Mansky-Kummert, Dipl.-Ing. Branislav Miskovic

    1 SWS   2 ECTS

    Lecture contents

    This course teaches programming concepts using the Python programming language. Knowledge of basic concepts and elemental programming experience are prerequisites. Fundamentals are repeated at the beginning of the course.
    Techniques like Debugging and Tools like Git for Version control are discussed.
    In addition, the following topics are discussed:
    * Data structures
    * Regular expressoins and search algorithms (A* algorithm, Beam search, ...)
    * Usage of Application Programming Interfaces (APIs), JSON, XML
    * Basics of Information Retrieval

    Assessment methods

    Continuous assessment
    Partial performances in the form of individual work, group work and presentations.
    Oral Final Exam.

    Teaching methods

    Lecture/Talk.

    Language

    English

    Programming and Algorithms for Language Technologies UE
    2 SWS
    4 ECTS

    Programming and Algorithms for Language Technologies UE

    Lector: Dipl.-Ing. Georg Mansky-Kummert, Dipl.-Ing. Branislav Miskovic

    2 SWS   4 ECTS

    Lecture contents

    This course teaches basic concepts of object-oriented programming using the Python programming language. Concepts of programming languages such as control structures, elementary data types, data structures, classes, objects and functions are taught. Furthermore, the design of programs, their analysis and techniques for debugging, tracing and testing are taught.
    The course covers the following topics in particular:
    - Basics of programming
    - Variables and data types
    - Operators
    - Control structures
    - Error handling
    - Basics of object orientation
    - Sorting algorithms
    - Search algorithms

    Assessment methods

    Continuous assessment
    Partial performances in the form of group work and presentations.

    Teaching methods

    Small group work, practical exercises, presentation of results.

    Language

    English

    Statistical Methods for Language Processing ILV
    2 SWS
    4 ECTS

    Statistical Methods for Language Processing ILV

    Lector: Dr. Christian Steineder

    2 SWS   4 ECTS

    Lecture contents

    - Probability
    - Analyzing, filtering and visualizing data
    - Testing hypotheses
    - Statistical estimators
    - Experiment Design
    - Approach to statistical projects

    Assessment methods

    Continuous assessment
    Activity in lectures and exercises: Participation in discussions, elaboration of exercise examples, own statistical project, written exam.

    Teaching methods

    Theory transfer in class, discussion of practical examples, own project

    Language

    English

    Translation Technologies VO
    2 SWS
    4 ECTS

    Translation Technologies VO

    2 SWS   4 ECTS

    Lecture contents

    - Introduction to different types of translation technologies from computer assisted translation (CAT) to automated machine translation.
    - Critical analysis of the perception of different technologies in the company and advantages and disadvantages of each technology
    - Overview of different tools and available systems in each technology
    - Overview of the current state of research and interesting open research questions in this larger topic area
    - Insights into methods of quality improvement from pre- and post-editing to the revision process in translation
    - Practical work with a system of computer-aided translation

    Assessment methods

    Continuous assessment
    Written final exam, practical exercises, presentations.

    Teaching methods

    Lecture/lecture, practical exercises, discussions, feedback, case solutions.

    Language

    English

    Basics in Machine Translation ILV
    3 SWS
    5 ECTS

    Basics in Machine Translation ILV

    3 SWS   5 ECTS

    Lecture contents

    - Introduction to the different approaches of machine translation from statistical to rule-based to neural and hybrid approaches.
    - Introduction to basic concepts and algorithms of statistical machine translation
    - Introduction to basic concepts and algorithms of neural machine translation
    - Critical analysis of the advantages and disadvantages of individual systems as well as the goal and purpose of the respective approaches
    - Basic knowledge of machine translation evaluation methods
    - Practical introduction to concrete translation models

    Assessment methods

    Continuous assessment
    Written final exam, practical exercises, presentations.

    Teaching methods

    Lecture/lecture, practical exercises, work assignments, discussions, feedback, case solutions.

    Language

    English

    Information Design for Language Data ILV
    2 SWS
    4 ECTS

    Information Design for Language Data ILV

    Lector: Dr-.tech Dipl-,Ing Ahmad Haj Mosa

    2 SWS   4 ECTS

    Lecture contents

    - Basics of information design
    - Target group oriented design of media and information
    - Design development on the basis of cognitive science principles
    - Basics of Gestalt and perception psychology
    - Methods of information design for different media
    - Applications in web, virtual and augmented reality etc.

    Assessment methods

    Continuous assessment
    Partial performance through active participation in discussions and the elaboration of exercise examples, own information design project, written examination.

    Teaching methods

    Teaching theory in class, interdisciplinary lecture series, discussion of practical examples; own information design project.

    Language

    English

    Information Extraction and Retrieval for Multilingual Natural Language Data ILV
    3 SWS
    6 ECTS

    Information Extraction and Retrieval for Multilingual Natural Language Data ILV

    Lector: Liad Magen

    3 SWS   6 ECTS

    Lecture contents

    - Retrieval models: boolean, vector space, probabilistic.
    - Representation of content: Free text search, documentation languages, special logics, indexing, etc.).
    - Machine-Learning-concepts and techniques: clustering, classification
    - Deep Learning in Information Retrieval
    - Web Retrieval: Link Analysis, Crawling, Search Engines

    Assessment methods

    Continuous assessment
    Partial performance through active participation in discussions and the elaboration of exercise examples, own IR project, written examination.

    Teaching methods

    Theory transfer in class, discussion of practical examples; own IR project

    Language

    English

    Machine Learning Methods for Language Processing VO
    1 SWS
    2 ECTS

    Machine Learning Methods for Language Processing VO

    Lector: DI Dr. techn. Mugdim Bublin

    1 SWS   2 ECTS

    Lecture contents

    - Critical analysis of classical ML algorithms.
    - Standard DL algorithms: CNN, RNN, Generative Networks
    - Modern DL architectures for Natural Language Processing (NLP): Attention, Transformer, GPT, BERT etc.
    - Applications of ML in general and DL in particular to NLP: text understanding, translation, speech and text generation, web search, knowledge generation
    - Limitations of DL

    Assessment methods

    Module exam

    Teaching methods

    Theoretical lessons, discussion of practical examples, own DL-project

    Language

    English

    Machine Learning Methods for Language Processing UE
    2 SWS
    4 ECTS

    Machine Learning Methods for Language Processing UE

    Lector: DI Dr. techn. Mugdim Bublin

    2 SWS   4 ECTS

    Lecture contents

    - Critical analysis of classical ML algorithms.
    - Standard DL algorithms: CNN, RNN, Generative Networks
    - Modern DL architectures for Natural Language Processing (NLP): Attention, Transformer, GPT, BERT etc.
    - Applications of ML in general and DL in particular to NLP: text understanding, translation, speech and text generation, web search, knowledge generation
    - Limitations of DL

    Assessment methods

    Module exam

    Teaching methods

    Theoretical lessons, discussion of practical examples, own DL-project

    Language

    English

    Speech Technologies ILV
    3 SWS
    6 ECTS

    Speech Technologies ILV

    3 SWS   6 ECTS

    Lecture contents

    - Speech Technologies and Automatic Speech Recognition (ASR)
    - Fundamentals of Phonetics and Phonology
    - Neural Networks for Speech Technologies
    - Introduction to dialogue systems
    - Practical introduction to ASR and speech-to-speech systems

    Assessment methods

    Final exam
    Written final examination, partial performance in the form of practical exercises.

    Teaching methods

    Lecture, practical exercises, presentations, discussions, feedback.

    Language

    English

    Transcultural Communication VO
    2 SWS
    3 ECTS

    Transcultural Communication VO

    2 SWS   3 ECTS

    Lecture contents

    - Transcultural communication from the perspective of different disciplines (with a focus on translation studies)
    - communication science basics intra-, inter- and multilingual barriers and transculturality
    - online collaborative translation as transcultural communication
    - conceptual issues and problems
    - technology assessment and ethical considerations
    - transcultural communication and translation in teams

    Assessment methods

    Final exam
    Final Written Exam.

    Teaching methods

    Lecture/lecture, discussion, case studies.

    Language

    English

    Academic Writing ILV
    2 SWS
    5 ECTS

    Academic Writing ILV

    2 SWS   5 ECTS

    Lecture contents

    - Systematic research and reception of scientific works
    - Correct citation
    - Language register: formal vs. informal
    - academic terminology and phrasing
    - Structure of a paragraph
    - Structure of a scientific paper
    - Linguistic presentation of the chosen method, achieved results and resulting discussion
    - describing statistical and qualitative data

    Assessment methods

    Final exam
    Writing and research exercises, written seminar paper.

    Teaching methods

    Writing and research exercises, correction tasks, feedback, discussion, problem-based learning.

    Language

    English

    Advanced Machine Translation ILV
    3 SWS
    5 ECTS

    Advanced Machine Translation ILV

    3 SWS   5 ECTS

    Lecture contents

    - Theoretical elaboration of different architectures in the field of neural machine translation.
    - Theoretical overview of the current state of research and interesting current research topics, e.g. machine translation with only little available training data
    - Critical discussion of advantages and disadvantages of the respective systems
    - Analysis and discussion of current practice regarding the application of machine translation systems in companies
    - Practical development of concrete current models of neural machine translation as well as their evaluation methods

    Assessment methods

    Continuous assessment
    Written final exam, practical exercises, presentations.

    Teaching methods

    Lecture/lecture, practical exercises, work assignments, discussions, feedback, case solutions.

    Language

    English

    Human-Computer Interaction for Computational Linguists ILV
    2 SWS
    4 ECTS

    Human-Computer Interaction for Computational Linguists ILV

    2 SWS   4 ECTS

    Lecture contents

    - Psychological aspects of HCI
    - Usability
    - User research
    - Benchmarking usability
    - Interaction design
    - Prototyping
    - Usability research and testing methods
    - Usability in practice

    Assessment methods

    Continuous assessment
    Case studies, group exercise, written final exam.

    Teaching methods

    Case studies, practical exercises, lecture

    Language

    English

    Software Engineering for Language Technologies ILV
    3 SWS
    6 ECTS

    Software Engineering for Language Technologies ILV

    3 SWS   6 ECTS

    Lecture contents

    Organizational possibilities for structuring software development in the form of process models, such as the waterfall model, spiral model and agile models, are presented. The technical aspects of software engineering focus on the creation of object-oriented systems and their modelling in the field of machine learning.
    The course covers the following topics in particular:
    - requirements engineering
    - use cases
    - High Level Design
    - Software engineering aspects in the area of machine learning
    - Selected UML diagrams
    - Process models

    Assessment methods

    Continuous assessment
    Group work, written final exam.

    Teaching methods

    Blended learning, guest lectures, experiential learning, coaching

    Language

    English

    Internship (10 ECTS nach Wahl)

    Internship FH Campus Wien MODUL
    2 SWS
    10 ECTS
    Internship Universität Wien MODUL
    2 SWS
    10 ECTS

    Data Protection and Privacy for Computational Linguists ILV
    1 SWS
    2 ECTS

    Data Protection and Privacy for Computational Linguists ILV

    1 SWS   2 ECTS

    Lecture contents

    - Introduction to the Austrian and European legal system
    - Introduction to data protection law
    - Protection of privacy and general protection of personality
    - Principles of processing personal data
    - Roles under data protection law
    - Data subject rights and obligations of the processor
    - Insight into data security concepts
    - Privacy by Design and Privacy by Default
    - E-Privacy
    - Basics of cyber security
    - Tasks and powers of the data protection supervisory authority and procedural aspects

    Assessment methods

    Continuous assessment
    - Activities during lectures and exercises: Participation in discussions
    - Participation
    - Written examination

    Teaching methods

    - Theory transfer in lectures
    - Discussion of practical examples

    Language

    English

    IT Project Management for Computational Linguists ILV
    1 SWS
    2 ECTS

    IT Project Management for Computational Linguists ILV

    1 SWS   2 ECTS

    Lecture contents

    Project management is the application of knowledge, skills, tools and techniques to project activities in order to meet project requirements. The project manager is responsible for meeting the expectations of the stakeholders in the project.
    The course covers in particular the following contents:
    - The immersion in the knowledge areas of project management (for example: Integration management, time management, cost management, quality management and risk management).
    - Project management across cultural boundaries
    - The management of virtual teams
    - Legal aspects in IT projects

    Assessment methods

    Continuous assessment
    Written final examination, preparation of a case study.

    Teaching methods

    Case studies, lecture

    Language

    English

    Master Kolloquium SE
    2 SWS
    4 ECTS

    Master Kolloquium SE

    2 SWS   4 ECTS

    Lecture contents

    - Refresher course on research methodology
    - Refresher and consolidation of good practice in scientific work
    - Presentation techniques and types for scientific work
    - Methods for the preparation of a master thesis concept

    Assessment methods

    Continuous assessment
    Oral presentation, written work in the form of an exposé.

    Teaching methods

    Group work, discussion, presentation, feedback, interactive lecture with practical exercises.

    Language

    English

    Master's Finals AP
    0 SWS
    2 ECTS

    Master's Finals AP

    0 SWS   2 ECTS

    Lecture contents

    - Presentation and discussion of the final thesis
    - subject discussion
    The defensio consists of the presentation and defence of the Master's thesis as well as an examination on its scientific environment and an examination covering a further examination subject from the compulsory modules which is to be substantially distinguished from the environment of the Master's thesis.

    Assessment methods

    Final exam
    Master exam

    Teaching methods

    Independent development

    Language

    English

    Master's Thesis MT
    0 SWS
    20 ECTS

    Master's Thesis MT

    0 SWS   20 ECTS

    Lecture contents

    - Independent work on a subject relevant topic based on the technical topics of the compulsory elective modules in the third semester at an academic level under the supervision of a supervisor
    - Elaboration of the master thesis

    Assessment methods

    Final exam
    Seminar paper

    Teaching methods

    Independent work supported by coaching

    Language

    English

    Number of teaching weeks:
    18 weeks per semester

    Class Schedule at the FH Campus Wien:
    Fridays (full day), occasionally Saturdays (full day).

    Electives
    Selection and participation according to available places. There may be separate admission procedures.


    After graduation

    As a graduate of this program, a wide range of professional fields and career opportunities are open to you. Find out where your path can lead you.

    These subject-specific competences as well as the acquired interdisciplinary and methodological competences qualify graduates for careers in the scientific as well as in the private sector. Depending on the personal specialization, various professional fields open up. The interdisciplinary character of the program qualifies students for various working areas: IT sector, consulting and human resources development.

    • language, translation and localization industry

    • language technology in the sense of language and text processing and translation technology

    • transcultural knowledge organization

    • language resource management

    • machine translation

      • multilingual product management

      • multilingual information processing

      • multilingual human-computer interaction

      • usability and data science


        Studying made easy

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        Time abroad

        Expertise, language skills, broadening horizons

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        Open Lectures
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        Center for academic writing
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        Intensive German course
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        Networking with graduates and organizations

        We work closely with renowned companies in commerce and industry, with universities, institutions and schools. This guarantees you contacts for employment or participation in research and development. In the course of exciting school cooperations, students may contribute to firing up pupils on topics such as our Bionics Project with the Festo company. You can find information about our cooperation activities and much more at Campusnetzwerk. It's well worth visiting the site as it may direct you to a new job or interesting event held by our cooperation partners!


        Contact

        Head of Degree Program

        Secretary's office

        Mgr. Andrea Slaminková

        Favoritenstraße 226, B.3.05 
        1100 Wien 
        +43 1 606 68 77-2130 
        +43 1 606 68 77-2139 
        mlt@fh-campuswien.ac.at

        Map main campus Favoriten (Google Maps

        Office hours during the semester

        Monday, Wednesday and Friday from 10.00 a.m. to 12.00 p.m. and 1.00 p.m. to 4.00 p.m.

        Master in cooperation with


        Downloads

        Infofolder Multilingual Technologies
        pdf, 134 KB
         

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