Einleitung
Der Modulkatalog hilft Ihnen bei der Planung Ihres Studiums, indem er Ihnen
eine Übersicht über alle Module Ihres Studienprogramms bietet.
Das Dokument enthält folgende Rubriken:
Der Modulkatalog ist ein Informationsdokument und nicht rechtsverbindlich.
Zu Beginn jedes Semesters wird eine aktuelle Version auf der Website der
Philosophischen Fakultät publiziert.
Übersicht über die Modulgruppen
Übersicht über die Module in den Modulgruppen
06B-7523e01Einführung in die Computerlinguistik
06B-7523i01Wissenschaftliche Vertiefung
Module in der Gruppe: Wissenschaftliche Vertiefung
| 06SM523-s21 |
[Seminar] |
Wahl |
6 ECTS |
06B-7523i02Kernbereich Computerlinguistik und Sprachtechnologie
06B-7523i04Praxis der Computerlinguistik und Sprachtechnologie
Katalog der Pflichtmodule, Wahlpflichtmodule und Wahlmodule
Der Katalog enthält Informationen zu jedem Pflicht- und Wahlpflichtmodul.
Zum Teil finden Sie auch Informationen zu Wahlmodulen (Modultitel in eckigen
Klammern). Beachten Sie, dass die Titel von Wahlmodulen semesterweise wechseln
können und dass oft weitere, nicht im Modulkatalog enthaltene Wahlmodule
angeboten werden. Diese und alle anderen semesterbezogenen Informationen
(wie Veranstaltungstitel, Termine, Dozierende, Informationen zur Buchung)
entnehmen Sie dem aktuellen Vorlesungsverzeichnis.
06SM523-001 Introduction to Language Technology
Moduldetails: 06SM523-001 Introduction to Language Technology
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Pflicht |
| ECTS |
3 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module provides an introductory overview of computational linguistics and language technology. It covers central tasks such as text encoding, tokenization, morphological and syntactic processing, sequence tagging, and text classification. Students are introduced to language models, conversational systems, information retrieval, multilingual technologies, and speech and vision applications. The module integrates theoretical concepts with practical demonstrations and includes discussion of accessibility-oriented tools and responsible AI. |
| Lernziel |
Students can:
1. explain core concepts, tasks, and methods in modern language technology.
2. apply fundamental NLP techniques such as tokenization, tagging, and text classification.
3. describe how language models, chatbots, information retrieval pipelines, multilingual models, and translation systems operate.
4. outline principles of speech processing, multimodal approaches, and accessibility-oriented technologies.
5. assess the capabilities and limitations of language technologies, including fairness and bias. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None. |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-002 Programming in Language Technology 1
Moduldetails: 06SM523-002 Programming in Language Technology 1
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Pflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the fundamentals of command line interfaces and programming. It covers core programming constructs such as control structures, data types, and basic principles of object-oriented programming. Theoretical instruction is combined with hands-on exercises in natural language processing and data analysis. Practical work focuses on applying algorithmic approaches to problems typically encountered in computational linguistics. |
| Lernziel |
Students can:
1. operate command line interfaces.
2. use control structures and data types effectively.
3. apply basic principles of object-oriented programming.
4. conduct data analysis and natural language processing tasks.
5. address real-world problems using algorithmic approaches. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None.
Attending the module "Introduction to Language Technology" in the same semester is highly recommended. |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-003 Mathematical Foundations for Language Technology 1
Moduldetails: 06SM523-003 Mathematical Foundations for Language Technology 1
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Pflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module reviews and strengthens the mathematical foundations required for understanding and developing methods in language technology. It covers essential concepts from logic, set theory, probability theory, descriptive statistics, combinatorics, analysis, linear algebra, and information theory, and highlights how these areas underpin core techniques in computational linguistics. The module introduces practical exercises to build mathematical intuition and to support the implementation and analysis of language technology systems. Students also work with computational tools to explore, analyze, and visualize data. |
| Lernziel |
Students can:
1. explain language technology methods using mathematical concepts from the covered areas.
2. use mathematical tools to design solutions to selected problems in language technology.
3. analyze and visualize data using computational methods. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None. |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% mid-term exam |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-004 Machine Learning for Language Technology
Moduldetails: 06SM523-004 Machine Learning for Language Technology
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Pflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the fundamental concepts and methods of machine learning as they apply to language technology. It covers both theoretical foundations and practical exercises, with particular emphasis on deep learning and neural network architectures. The module presents logistic regression, multilayer perceptrons, recurrent neural networks, and Transformers. Students implement basic architectures and apply machine learning techniques to selected tasks in language technology. |
| Lernziel |
Students can:
1. explain key concepts in machine learning.
2. compare different machine learning approaches including logistic regression, MLPs, RNNs, and Transformers.
3. implement basic machine learning architectures.
4. design solutions to selected language technology problems using machine learning. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Mathematical Foundations for Language Technology 1" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio: 80% final exam, 20% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-005 Programming in Language Technology 2
Moduldetails: 06SM523-005 Programming in Language Technology 2
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Pflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module deepens programming skills in Python with a focus on developing software for language technology applications. It emphasizes writing clear and maintainable code, applying modern programming techniques to domain-specific tasks, and using essential practices in code management such as version control, testing, debugging, and systematic code review. Integrated exercises support the refinement and evaluation of software in natural language processing contexts. |
| Lernziel |
Students can:
1. apply modern programming knowledge and skills to solve tasks in language technology.
2. review, debug, and improve human- and machine-written code in language technology applications.
3. use essential code management practices, including version control and testing, to support systematic software development. |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
Successfully completed module "Programming in Language Technology 1" or equivalent knowledge. Knowledge to the extent of "Introduction to Language Technology". |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-101 Introduction to Experimental Research
Moduldetails: 06SM523-101 Introduction to Experimental Research
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the process of designing and administering experimental research studies in linguistics and language technology. It covers the formulation of research questions and hypotheses, experimental design, the developlemt of tasks and stimulus materials, and key considerations for participant recruitment. The module also introduces a range of methodologies used to collect linguistic data in different modalities, with a special focus on the linguistic lab infrastructure available at UZH. Finally, the module addresses the administration of studies as well as the postprocessing and interpretation of empirical data. It provides an early foundation for the research cycle and supports later coursework on the modeling of experimental data, scientific writing and ethical conduct. |
| Lernziel |
This module introduces the process of designing and administering experimental research studies in linguistics and language technology. It covers the formulation of research questions and hypotheses, experimental design, the developlemt of tasks and stimulus materials, and key considerations for participant recruitment. The module also introduces a range of methodologies used to collect linguistic data in different modalities, with a special focus on the linguistic lab infrastructure available at UZH. Finally, the module addresses the administration of studies as well as the postprocessing and interpretation of empirical data. It provides an early foundation for the research cycle and supports later coursework on the modeling of experimental data, scientific writing and ethical conduct. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None.
The module is complemented by the module "Scientific Writing and Ethical Conduct" offered in a later semester that deals with the subsequent stages of the research process, specifically, writing up the research results and publishing data, models, and code. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-102 Introduction to Speech and Voice Processing
Moduldetails: 06SM523-102 Introduction to Speech and Voice Processing
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces students to the fundamentals of machine and human speech and voice processing. It covers essential principles of digital audio signal processing and their application to tasks such as speech recognition, voice identification, and speech synthesis. Students learn how acoustic modelling and feature extraction techniques are used in computational systems and how these approaches differ from human perception and processing of speech and voice signals. The module establishes the conceptual and technical foundations required for subsequent modules in speech and voice technology. |
| Lernziel |
This module introduces students to the fundamentals of machine and human speech and voice processing. It covers essential principles of digital audio signal processing and their application to tasks such as speech recognition, voice identification, and speech synthesis. Students learn how acoustic modelling and feature extraction techniques are used in computational systems and how these approaches differ from human perception and processing of speech and voice signals. The module establishes the conceptual and technical foundations required for subsequent modules in speech and voice technology. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None. |
| Leistungsnachweis |
Portfolio: 75% written exam, 25% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-103 Introduction to Visual Language Processing
Moduldetails: 06SM523-103 Introduction to Visual Language Processing
| Modulgruppe |
Einführung in die Computerlinguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the foundations of automatic visual language processing. It covers image and video processing, visual prosody in spoken and sign languages, and the automatic analysis and synthesis of visual cues in speech and sign languages. The module combines theoretical instruction with practical exercises. |
| Lernziel |
This module introduces the foundations of automatic visual language processing. It covers image and video processing, visual prosody in spoken and sign languages, and the automatic analysis and synthesis of visual cues in speech and sign languages. The module combines theoretical instruction with practical exercises. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Programming in Language Technology 1" or equivalent knowledge. Knowledge to the extent of "Introduction to Language Technology". |
| Leistungsnachweis |
Portfolio: 75% written exam, 25% proof of self-study achievements |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s21 [Seminar]
Moduldetails: 06SM523-s21 [Seminar]
| Modulgruppe |
Wissenschaftliche Vertiefung |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Seminar |
| Allgemeine Beschreibung |
This module provides in-depth engagement with a specific topic in language technology. Students learn scientific working methods, including analyzing research literature, interpreting empirical results, and evaluating theoretical approaches. They prepare and deliver a scientific presentation and write a paper expanding on their topic. |
| Lernziel |
Students can:
1. gain insight into a specific area of language technology.
2. acquire methodological skills for scientific research.
3. present complex topics clearly.
4. write a scientific paper." |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Written paper and presentation |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-111 Fundamentals of Large Language Models
Moduldetails: 06SM523-111 Fundamentals of Large Language Models
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the fundamental ideas underlying large language models (LLMs) and their importance in research, industry, and language technology. It covers core concepts such as training objectives and model architectures and examines techniques that enhance the problem-solving abilities of LLMs, including reasoning and tool use. The module also discusses engineering methods that enable LLMs to scale to large datasets and parameter counts. |
| Lernziel |
Students can:
1. explain how LLMs work and how they are developed.
2. apply LLMs to selected language technology tasks.
3. evaluate LLM performance systematically.
4. discuss the state of the art in LLM research and applications. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Machine Learning for Language Technology" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-112 Language Technology with Multilingual and Multimodal Data
Moduldetails: 06SM523-112 Language Technology with Multilingual and Multimodal Data
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces key methods for multilingual and multimodal modeling in language technology. It examines longstanding tasks such as transforming text between languages in machine translation and converting audio recordings into text in speech recognition, and shows how multilingual and multimodal approaches can be beneficial even for tasks confined to a single language or modality, particularly in low-resource settings. The module discusses methods developed for mapping between languages and modalities and explains how shared internal representations support cross-lingual and cross-modal transfer. In addition, students analyze the practical consequences of these approaches, including positive transfer effects as well as undesirable biases that can arise from multilingual or multimodal systems. |
| Lernziel |
Students can:
1. build multilingual and multimodal language technology applications.
2. explain common methods for mapping between languages and modalities, such as those used in machine translation and related tasks.
3. describe how shared internal representations enable cross-lingual and cross-modal transfer.
4. analyze benefits and limitations of multilingual and multimodal modeling, including transfer effects and biases. |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
Successfully completed modules "Machine Learning for Language Technology" and "Programming in Language Technology" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-113 Mathematical Foundations for Language Technology 2
Moduldetails: 06SM523-113 Mathematical Foundations for Language Technology 2
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module deepens the mathematical foundations required in computational linguistics and machine learning. It focuses on central concepts in linear algebra, analysis, and probability theory, emphasizing conceptual understanding and formal reasoning. Lectures are accompanied by written exercises that reinforce both theoretical comprehension and practical application. |
| Lernziel |
This module deepens the mathematical foundations required in computational linguistics and machine learning. It focuses on central concepts in linear algebra, analysis, and probability theory, emphasizing conceptual understanding and formal reasoning. Lectures are accompanied by written exercises that reinforce both theoretical comprehension and practical application. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Mathematical Foundations for Language Technology 1". |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-114 Scientific Writing and Ethical Conduct
Moduldetails: 06SM523-114 Scientific Writing and Ethical Conduct
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces students to research ethics and data protection in the context of sharing and publishing data, models, and code. It also covers conventions of scientific writing, focusing on research in language and speech technology. Topics include preparing datasets, models, and code for open research, literature management, and the writing of scientific texts such as theses and conference papers. The module also addresses responsible use of generative AI in scientific writing. |
| Lernziel |
Students can:
1. identify important aspects of data, model, and code sharing.
2. write scientific texts that follow common conventions and use generative AI responsibly.
3. communicate research outcomes clearly and accessibly. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None.
The best time to attend this module is following the completion of a seminar or programming project and before starting the bachelor's thesis. In that case, the seminar or programming project and a potential write-up can serve as a starting point for the tasks of this module. The module can also be attended without this prior work.
Prior attendance of the module "Introduction to Experimental Research" is recommended. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-115 Software Lab
Moduldetails: 06SM523-115 Software Lab
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module treats software development as a collaborative team process. It focuses on the development of language technology applications using a combination of technologies, including web interfaces, AI models, databases, and data visualizations. A special focus is placed on the creative process: collaborating effectively with team members, turning an initial idea into a working prototype, and presenting the result to an audience. |
| Lernziel |
Students can:
1. collaborate in a small team to design and implement a software project in language technology.
2. demonstrate a prototype to an audience.
3. document the project in a written report and reflect on the creative process.
4. provide constructive, actionable feedback to peers.
5. independently acquire technical skills needed for their project, such as software development tools, web technologies, and data modelling. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed modules "Programming in Language Technology 1" and "2" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s11 [Focus course: Cognitive Modeling]
Moduldetails: 06SM523-s11 [Focus course: Cognitive Modeling]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module focuses on modeling behavioral and neurophysiological data to (i) gain insights into the cognitive mechanisms underlying human language processing and (ii) advance technological applications, such as human-centric natural language processing (NLP). It provides an interdisciplinary perspective by introducing a range of modeling approaches, from computational cognitive process models to recent machine learning techniques. Through a combination of theoretical input and practical exercises, students develop a deeper understanding of human language processing and how it can be modeled for both fundamental research and technological applications. |
| Lernziel |
Students can:
1. deepen their knowledge of computational models of human language processing for both cognitive research and technological applications.
2. explain and implement models that process human behavioral and neurophysiological data. |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
Successfully completed module "Introduction to Experimental Research"; Successfully completed module "Programming in Language Technology 1" or equivalent knowledge. Successfully completed module "Mathematical Foundations for Language Technology 1". |
| Leistungsnachweis |
Portfolio: 75% written exam, 25% proof of self-study achievements |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s12 [Focus course: Digital Accessibility]
Moduldetails: 06SM523-s12 [Focus course: Digital Accessibility]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module provides an in-depth overview of the barriers encountered by persons with disabilities-such as blindness or visual impairment, deafness or hearing impairment, cognitive or motor impairments, and speech and language disorders-when accessing information and communication. The module provides an overview of common barriers and introduces language-based assistive technologies and e-accessibility measures. The accompanying exercises offer hands-on practice with a range of relevant tools and techniques. |
| Lernziel |
Students can:
1. identify different target groups in accessibility contexts.
2. describe barriers that these groups face when accessing information, communication, and related technologies.
3. explain tools and measures that help reduce selected accessibility barriers.
4. operate selected accessibility-related tools. |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
Successfully completed module "Introduction to Experimental Research"; Successfully completed module "Programming in Language Technology 1" or equivalent knowledge. Successfully completed module "Mathematical Foundations for Language Technology 1". |
| Leistungsnachweis |
Portfolio: 75% written exam, 25% proof of self-study achievements |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s13 [Focus course: Speech]
Moduldetails: 06SM523-s13 [Focus course: Speech]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module focuses on advanced topics in human and machine speech and voice processing. It covers core principles of acoustic modelling, feature extraction, and computational methods used in applications such as speech recognition, speech synthesis, and voice identification. Students also explore how humans produce and perceive speech and voice, allowing for a comparative understanding of biological and computational systems. The module integrates theoretical perspectives with practical work using speech and voice processing tools. It is designed to deepen students' knowledge of speech communication and prepare them for engagement with current scientific questions in the field. |
| Lernziel |
Students can:
1. deepen their knowledge in selected areas of human and machine speech and voice processing.
2. strengthen methodological skills for analyzing and working with speech and voice data.
3. evaluate contemporary scientific questions related to speech and voice communication. |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
Successfully completed module "Introduction to Speech and Voice Processing" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s14 [Focus course: Text Technology]
Moduldetails: 06SM523-s14 [Focus course: Text Technology]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module focuses on core technologies and tasks in text technology, including text mining, machine translation, language modeling, and text analytics. The module introduces key methods used in these areas and discusses central challenges that arise when processing and analyzing large collections of textual data. Through a combination of theoretical input and practical exercises, students deepen their understanding of the techniques and considerations that shape modern text technology applications. |
| Lernziel |
Students can:
1. deepen their knowledge in selected areas of text technology.
2. explain and implement key methods used in text technology. |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
Successfully completed module "Introduction to Language Technology" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s15 [Excursion]
Moduldetails: 06SM523-s15 [Excursion]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
3 |
| Lehrform |
Exkursion |
| Allgemeine Beschreibung |
Excursions, similar to practical training off-site, offer the opportunity to gain insight into the daily work of computional linguists. In contrast to these, however, the emphasis is not on concrete work in a company, but on the ability to recognize and assess the problems and methods of a field of application of computational linguistics in direct contact as accurately as possible. This provides insights into problem areas, allows one to measure one's own specific interests and, if necessary, to fix future work areas and employers. The students prepare for the excursion by effectively researching and studying relevant literature. This module can be booked to credit the participation in excursions. |
| Lernziel |
The students (1) gain insight into language technology companies and university or non-university research departments (2) get to know the theory and practice of computational linguistics in a concrete example (3) find or develop one's own specific interests (4) gain the ability to get insight into practical problems and methods through interviews with practitioners (5) get in contact with potential employers |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
This module can not be booked by the students themselves, the booking has to be authorized by the module coordinator. In order to credit the participation in an excursion, it is essential to contact to the module coordinator before the start of the excursion. |
| Leistungsnachweis |
Nachweis von im Selbststudium erbrachten Studienleistungen |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s16 [Summer School]
Moduldetails: 06SM523-s16 [Summer School]
| Modulgruppe |
Kernbereich Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahl |
| ECTS |
3 |
| Lehrform |
|
| Allgemeine Beschreibung |
This module allows students to deepen their knowledge in specific areas of language technology by attending a summer school. Students consolidate prior learning, engage with core theories, explore new approaches, learn about current trends, and exchange experiences with students from other institutions.
This module can be booked for 3 or 6 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. consolidate previously learned material.
2. acquire new content in a compact format.
3. identify current trends.
4. exchange experiences with students from other universities.
5. develop international networks. |
| Unterrichtssprache |
English |
| Voraussetzungen |
This module can not be booked by the students themselves, the booking has to be authorized by the module coordinator. In order to credit the attendance at a summer school, it is essential to submit a request to the module coordinator before the start of the summer school. |
| Leistungsnachweis |
Evidence of study achievements during Summer School |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
03SM22AINF01 Informatik und Wirtschaft (V) (Informatics and the Economy)
Moduldetails: 03SM22AINF01 Informatik und Wirtschaft (V) (Informatics and the Economy)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung |
| Allgemeine Beschreibung |
Computer haben unser Leben tiefgreifend verändert. Um die heutige Gesellschaft und Wirtschaft und deren stetigen Veränderungen zu verstehen, muss man wissen, wie Computer funktionieren. Das Ziel der Vorlesung Informatik und Wirtschaft ist es, Ihnen eine Basis zu vermitteln, um unsere informationstechnisch gesteuerte Welt zu verstehen und darin erfolgreich zu sein. |
| Lernziel |
Um die heutige Gesellschaft und Wirtschaft als Ganzes zu begreifen, muss man verstehen, wie Computer funktionieren und wie sie unser wirtschaftliches Umfeld verändern. Ziel der Vorlesung Informatik für Ökonomen ist es, diese zwei Bereiche zu beleuchten.
Zunächst beschäftigen wir uns also mit der Frage wie Computer und Informationssysteme funktionieren. Dabei werden wir ergründen auf welchen Prinzipien die Geräte basieren und wie diese programmiert werden können.
- Wie funktioniert ein Computer wie z. B. mein Smartphone?
- Was sind die technischen Grundlagen für die Vielzahl von Informationen
auf dem Web?
Als weiteres wollen wir verstehen, wie sich Informationssysteme auf unser wirtschaftliches Umfeld auswirken.
- Weshalb lohnt es sich in Computer zu investieren?
- Welchen Mehrwert leisten diese für eine Firma?
- Wie, wo, und mit welcher Zielsetzung werden und sollen Computer demnach in Firmen und Organisationen eingesetzt werden?
- Warum haben Supermarktketten und Warenhäuser moderne Scannerkassen eingeführt?
- Welche Besonderheiten haben Digitale Güter -- also Produkte, die nur aus einer Ansammlung von Daten bestehen, wie Musik, Filme, oder Software -- und wie wirken sich diese auf deren Handel aus? |
| Unterrichtssprache |
Deutsch |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22AINF02 Informatics I (L+E) (Informatik I)
Moduldetails: 03SM22AINF02 Informatics I (L+E) (Informatik I)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
The lecture gives an introduction to programming. The students learn to use the computer as a tool for creating software. Based on the programming language "Python", basic concepts in programming, such as variable assignment, control structures, classes and objects, as well as advanced subjects such as inheritance and polymorphism are taught.
The theoretical concepts taught in the lecture are augmented with numerous examples, demonstrating the practical application of the presented concepts.
The students also receive regular assignments to practice writing programs individually throughout the semester. |
| Lernziel |
By successful participation, the students obtain competence in the following areas:
* Analyzing problem statements towards writing software
* Designing programs and algorithms
* Writing software
* Basic concepts of hard- and software |
| Unterrichtssprache |
The primary lecture language is English. All materials (slides, exercises, and exams) are in English. |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22AINF04 People-Oriented Computing (L+E) (Mensch und Computer)
Moduldetails: 03SM22AINF04 People-Oriented Computing (L+E) (Mensch und Computer)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
Developments in technology have had a profound impact on people and the world in which we live, work, and interact. These developments are simultaneously enabling and challenging, and the co-evolution of computing and people's use of it has led to important issues for the design, development, adoption of technology, as well as the understanding of its impact on how we live.
This course provides an introduction to human-oriented aspects of computing, and serves as a foundation for further study in people- oriented computing. Fundamental human issues of technology will be covered at the level of individuals, groups, organizations, and society.
The course will provide a general introduction to key areas in people- oriented computing, and also touch upon relevant topics such as roles and potential careers in computing, methods and approaches employed in these areas, and future directions for technology. |
| Lernziel |
Students should gain familiarity with various topics related to people- oriented computing, including important challenges and questions relating to computing at the human, group, organizational, and societal levels. They should have an understanding of connections between technological and human issues. |
| Unterrichtssprache |
English and German |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BI0001 Foundations of Computing II (L+E)
Moduldetails: 03SM22BI0001 Foundations of Computing II (L+E)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
Required second-year course covering topics from discrete math and formal methods building the foundations of computing. The material of this course is pervasive in the areas of algorithms, data structures and programming but appears virtually in all areas of computer science as well. The course will cover topics such as, but not limited to, proof methods, formal languages, deterministic and nondeterministic finite automata, grammars and pushdown automata, Turing machines, computability, decidability and complexity, P and NP, NP-completeness. |
| Lernziel |
The goal of the course is to familiarize the student with formal methods of computing and their value for computer science and related disciplines, and to provide basic training in applying formal methods to many different kinds of problems. Students should learn the fundamental limits of computation and extend their knowledge on formal languages as well as on formal programming models. Principles of interference, deduction, induction and contradiction should regularly be applied to demonstrate the formal correctness of models and limits. |
| Unterrichtssprache |
English |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BI0003 Numerical Methods in Informatics (L+E)
Moduldetails: 03SM22BI0003 Numerical Methods in Informatics (L+E)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
The course presents the basic numerical and linear algebra techniques to solve mathematical problems that arise in computer science. The topics cover a wide range such as e.g.: basic concepts of scientific programming, solution of systems of linear equations and of nonlinear equations; interpolation and least-square approximation of data and functions; eigenvalues and eigenvectors computation; integration and differentiation and numerical optimization.
The course consists of lectures, exercises and homework assignments. |
| Lernziel |
By the end of the course, the students will be able to identify a suitable method to solve basics problems of scientific computing, understand the main implications of the method and implement it directly or apply it using existing libraries. The students will learn how to solve such problems and to implement required algorithms and solutions in Python. The course will provide to the students the basis to understand more complex numerical tools that they may encounter in future courses or in their professional career. |
| Unterrichtssprache |
English |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BI0004 Software Construction (L+E) (Softwarekonstruktion)
Moduldetails: 03SM22BI0004 Software Construction (L+E) (Softwarekonstruktion)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
Knowing how to program does not make a student a software designer. The next step involves learning and practicing the fundamental principles and techniques for designing long-lived software systems. This course helps students learn software design by building examples of small versions of tools that programmers use every day. The course includes a practical component, highlighting the
engineering skills needed to design robust software systems. Primarily, the course is taught using Python, with the final lectures introducing Java. |
| Lernziel |
As a result of this course, students will acquire:
A solid understanding of the principles and techniques of modern software design, including:
A.1 Concepts and issues of software quality and maintainability
A.2 Code as data
A.3 Object-oriented programming
A.4 Fundamental design patterns (recognized best practices of software architectures)
A.5 Fundamentals of software testing
A.6 Fundamentals of modern software engineering tools
B. Experience in collaborative tasks applying these principles and techniques |
| Unterrichtssprache |
English |
| Voraussetzungen |
Informatics I (or equivalent) |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BI0005 Wirtschaftsinformatik II (V+Ü) (Business Informatics II)
Moduldetails: 03SM22BI0005 Wirtschaftsinformatik II (V+Ü) (Business Informatics II)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
- Die Vorlesung behandelt Prozessmanagement und ERP Systeme. Sie hat folgenden Aufbau: Einführung in die Lehrveranstaltung
- Prozesse
- Business Process Model and Notation (BPMN)
- Strategisches Prozessmanagement
- Ist/Soll-Modellierung
- Implementierung
- Process Mining
- Enterprise Resource Planning (ERP)
- Organisatorische Implementierung
- Die begleitenden Übungen behandeln das Modellieren von BPMN, die Ist/Sollmodellierung, die Implementierung mit einer Process Engine sowie die Nutzung von ERPSim. Projektaufgabe.
|
| Lernziel |
Lernziel 1: Betrieblich Prozesse analysieren, modellieren, implementieren und managen können.
Lernziel 2: ERP Systeme nutzen und implementieren können. (ERP = Enterprise Ressource Planning) |
| Unterrichtssprache |
Deutsch; Hintergrundliteratur und Software kann auf Englisch sein |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BI0006 Computer Networks and Distributed Systems (L+E) (Kommunikationsnetze und Verteilte Systeme)
Moduldetails: 03SM22BI0006 Computer Networks and Distributed Systems (L+E) (Kommunikationsnetze und Verteilte Systeme)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
The Information and Communications Technology (ICT) age has arrived within our daily life, not only during work and business hours, but at a good deal of entertainment and social interactions, too. Thus, the society has to cope with such
developments of digitization. Many of those human-centric statements only refer to or try to analyze the impact of these changes and the society. However, in very many cases the fundamentals to derive reliable, correct, and transparent conclusions requires a detailed know-how of Communication Networks and Distributed Systems (CNDS). Therefore, once stand-alone systems are discussed, their interconnection across physical boundaries of an office or building site forms the major development of the ICT society. While fundamental communication architectures did introduce communications by technical means, achieved over the past 100 years, the development of telephone communications to today's Internet will be covered. Protocols, reliable, unreliable, and secure services, algorithms for finding the corresponding receiver, routing, and basic mechanisms for Internet operations will form this lecture's part one.
Furthermore, once stand-alone systems have been interconnected, they constitute Distributed Systems, which form a collection of independent computers that appear to their users as a single coherent system, embedding hardware, within which all machines are fully autonomous, and software, for which users think they deal with a single system. Thus, basic theory and techniques of Distributed Systems are covered in this lecture's part two. Driven by an introduction, naming principles and distributed file systems are outlined. To ensure an application-driven interoperability, approaches for synchronization and coordination are discussed. Examples of Distributed Systems in use are overviewed. Finally, part three will overview the role of security in Computer Networks and Distributed Systems concludes this class. |
| Lernziel |
Students will receive the required insights into basic foundations on Communication Networks and Distributed Systems. More specifically, the lecture will teach communication architectures, network building blocks, shared links, packet switching, end-to-end protocols, selected Internet applications, naming principles, distributed file systems synchronization, coordination, and basic security elements as well as mechanisms. Overall, students will be able to understand which communication systems exist, how Internet-based systems operate world-wise, which communications can be reliable, how the basic inter-operations of Distributed Systems work, and which ones may be secured. |
| Unterrichtssprache |
English |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
03SM22BMI003 Requirements Engineering I (L+E)
Moduldetails: 03SM22BMI003 Requirements Engineering I (L+E)
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
Specifying requirements is a crucial prerequisite for successful software development.
This course gives an introduction to the principles, practices, languages, methods, processes, and tools for specifying and managing requirements. |
| Lernziel |
The students acquire basic knowledge, understanding and skills in the core principles, practices, languages, methods, and processes of Requirements Engineering. |
| Unterrichtssprache |
English |
| Voraussetzungen |
Basic knowledge of software development and modeling. Having taken a course in Software Engineering or read a SE textbook is strongly recommended.
Students enrolled in the BSc in Informatics program must have passed the assessment level successfully. |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Viertelschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Wirtschaftswissenschaftliche Fakultät |
07SMMAT141 MAT 141 Lineare Algebra für die Naturwissenschaften
Moduldetails: 07SMMAT141 MAT 141 Lineare Algebra für die Naturwissenschaften
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
5 |
| Lehrform |
Übung, Vorlesung, Wiederholungsprüfung |
| Allgemeine Beschreibung |
Einführung in die Lineare Algebra:
1. Lineare Gleichungssysteme: Gauss-Algorithmus
2. Matrizen: Rechenregeln, Inverse einer regulären Matrix, symmetrische Matrizen
3. Determinanten: Definition und Eigenschaften, Zusammenhang mit dem Lösen von Gleichungssystemen
4. Komplexe Zahlen
5. Vektorräume über den reellen/komplexen Zahlen: Unterraum, Basis, Dimension, Orthogonalität
6. Lineare Abbildungen und deren Zusammenhang mit Matrizen, Koordinatentransformation
7. Eigenwertprobleme: Eigenwerte, Eigenvektoren, Eigenwertproblem von symmetrischen Matrizen
8. Einführung in die Theorie der Differentialgleichungen |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Mathematisch-naturwissenschaftliche Fakultät |
07SMPHY231 PHY 231 Datenanalyse
Moduldetails: 07SMPHY231 PHY 231 Datenanalyse
| Modulgruppe |
Informatik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Übung, Vorlesung |
| Allgemeine Beschreibung |
This course provides the basics of data analysis for the physical sciences, focussing on statistics. The course covers the following topics:
* Bayesian and frequentist probability
* Statistical and systematic uncertainties
* Probability distribution functions (PDFs)
* Correlation and covariance
* Error propagation
* Hypothesis testing
* Least squares fitting
* Maximum likelihood method
* Confidence and credibility
The course is structured with weekly 45 min lectures along with 2 hr exercises in python in the afternoon. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Siehe Vorlesungsverzeichnis |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Mathematisch-naturwissenschaftliche Fakultät |
06SM523-131 Practical Training In-House
Moduldetails: 06SM523-131 Practical Training In-House
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Praktikum |
| Allgemeine Beschreibung |
This module provides students with practical experience in scientific project work. Activities include reading research literature, preparing and annotating data, applying statistical and machine learning methods, and contributing to workshop and conference papers. Students work on a defined subproblem within a scientific project.
This module can be booked with 6 or 9 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. gain practical experience in research.
2. read scientific literature.
3. contribute to evaluation processes.
4. complete assigned project tasks.
5. contribute to preparing scientific publications.
6. deepen topic-specific skills. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
This module cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. There is no entitlement to this module, the module will only be offered if a suitable position is available in a project. The requirements will be defined according to the topic. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-132 Practical Training Off-Site
Moduldetails: 06SM523-132 Practical Training Off-Site
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Praktikum |
| Allgemeine Beschreibung |
This module provides students with practical experience applying language technology in professional settings. Students gain insight into organizational structures, participate in software development tasks, and apply knowledge from their studies to real-world problems. The training takes place in companies or public organizations connected to language technology.
This module can be booked for 3 or 6 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. gain experience in language technology companies.
2. connect theoretical knowledge with practical work.
3. understand organizational structures and processes.
4. apply what they have learned in real settings.
5. broaden their understanding of practical issues. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
This module cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. A prior application must be approved by the module coordinator in order for the Practical Training Off-Site to be credited. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-133 Programming Project 1
Moduldetails: 06SM523-133 Programming Project 1
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Selbststudium |
| Allgemeine Beschreibung |
This module focuses on developing programming and software engineering skills through an extended project. Students define milestones, acquire and annotate data, implement a program, and evaluate it using appropriate methods. It is used to credit substantial project work.
This module can be booked for 3, 6 or 9 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. design a programming project.
2. carry out a project plan.
3. use existing tools.
4. apply software engineering practices.
5. document their work according to standards.
6. evaluate results.
7. use software repositories. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
In the duration of a study level a maximum of two programming projects can be booked. This module can be booked to credit work done in a programming project. It cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. Before a programming project is started, it is essential to get the permission of the module coordinator (per Email). The prerequisites will be set according to the topic. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-134 Programming Project 2
Moduldetails: 06SM523-134 Programming Project 2
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Selbststudium |
| Allgemeine Beschreibung |
This module consolidates programming and software engineering skills through an extended project. Students define milestones, acquire or annotate data, implement a program, and evaluate it. It is used to credit substantial project work.
This module can be booked for 3, 6 or 9 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. design a programming project.
2. carry out the project plan.
3. use existing tools.
4. apply software engineering principles.
5. document work according to standards.
6. evaluate results.
7. use software repositories. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
In the duration of a study level a maximum of two programming projects can be booked. This module can be booked to credit work done in a programming project. It cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. Before a programming project is started, it is essential to get the permission of the module coordinator (per Email). The prerequisites will be set according to the topic. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-135 Student Teaching Assistant 1
Moduldetails: 06SM523-135 Student Teaching Assistant 1
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Sonstiges |
| Allgemeine Beschreibung |
This module introduces students to foundational didactic skills through work as a tutor or teaching assistant. Students deepen their understanding of subject-specific content by preparing learning materials, designing assignments, correcting work, and reflecting on teaching practice.
This module can be booked for 3 or 6 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. understand subject-specific content from a teaching perspective.
2. prepare lecture content for specific target groups.
3. design exercise materials.
4. correct student work and provide constructive feedback. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Within a study programme, at most two modules of this types can be booked, whereby the two modules must differ in content. You must apply for this module. It is essential to contact the module coordinator or lecturers beforehand (by e-mail). Tutor positions are usually advertised on the computational linguistics mailing list (cl-list@lists.ifi.uzh.ch) during the term break. Students are also welcome to reach out at any time to the lecturers for whose course they would like to take on a tutorial. For tutorials, the corresponding module itself must have been successfully completed. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-136 Student Teaching Assistant 2
Moduldetails: 06SM523-136 Student Teaching Assistant 2
| Modulgruppe |
Praxis der Computerlinguistik und Sprachtechnologie |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Sonstiges |
| Allgemeine Beschreibung |
This module introduces students to foundational didactic skills through work as a tutor or teaching assistant. Students deepen their understanding of subject-specific content by preparing learning materials, designing assignments, correcting work, and reflecting on teaching practice.
This module can be booked for 3 or 6 ECTS points, determined in consultation with the module coordinator. |
| Lernziel |
Students can:
1. understand subject-specific content from a teaching perspective.
2. prepare lecture content for specific target groups.
3. design exercise materials.
4. correct student work and provide constructive feedback. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Within a study programme, at most two modules of this types can be booked, whereby the two modules must differ in content. You must apply for this module. It is essential to contact the module coordinator or lecturers beforehand (by e-mail). Tutor positions are usually advertised on the computational linguistics mailing list (cl-list@lists.ifi.uzh.ch) during the term break. Students are also welcome to reach out at any time to the lecturers for whose course they would like to take on a tutorial. For tutorials, the corresponding module itself must have been successfully completed. |
| Leistungsnachweis |
Documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
Ende
