| 1 | Aphasiology | LTC018M05 |
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| 2 | Basic Statistics | LTR013M05 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. H. Loerts | | Docent(en) | dr. H. Loerts | | Onderwijsvorm | computerpracticum, werkcollege | | Toetsvorm | schriftelijk tentamen, wekelijkse opdrachten | | ECTS | 5 |
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| 3 | Computational Semantics | LIX021M05 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | L. Abzianidze, PhD. | | Docent(en) | L. Abzianidze, PhD. | | Onderwijsvorm | hoorcollege, practicum | | Toetsvorm | programmeeropdrachten, schriftelijk tentamen, wekelijkse opdrachten | | ECTS | 5 |
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| 4 | Computational Simulations of Language | WMCC009-05 |
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| Faculteit | Science and Engineering | | Voertaal | Engels | | Coordinator | dr. J.K. Spenader | | Docent(en) | | | Onderwijsvorm | Practisch werk (PRC), Hoorcollege (LC) | | Toetsvorm | Opdracht (AST) | | ECTS | 5 |
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| 5 | Computer-Mediated Communication | LIX022M05 |
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| 6 | Corpus Linguistics | LTR024M05 |
In de cursus worden standaard technieken aangereikt voor het gebruik van corpora in taalkundig
onderzoek. Diverse corpora en corpusannotaties worden besproken. Praktische methoden in R voor het
zoeken en tellen van taalkundige patronen in corpora maken deel uit van de colleges. Ook zullen we
een aantal eenvoudige statistische methoden belichten die vaak worden gebruikt in onderzoek in de
corpustaalkunde. |
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| 7 | Debates in Linguistics | LLS044M10 |
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| 8 | DeSeGAIP | LTC021M06 |
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| 9 | Designing your Research Project | LTR021M05 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. C.S. Gooskens | | Docent(en) | dr. C.S. Gooskens | | Onderwijsvorm | werkcollege | | Toetsvorm | presentatie, wekelijkse opdrachten, werkstuk(ken) | | ECTS | 5 |
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| 10 | Discourse Analysis | LTR027M10 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | prof. dr. J.M. Fuller | | Docent(en) | | | Onderwijsvorm | werkcollege | | Toetsvorm | nog niet bekend | | ECTS | 10 |
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| 11 | DisDev | LTC019M05 |
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| 12 | Experimental Pragmatics | LTR025M10 |
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| Faculteit | Letteren | | Voertaal | Engels | | Docent(en) | G.J. Mills, PhD.prof. dr. G. Redeker | | Onderwijsvorm | werkcollege | | Toetsvorm | schriftelijke opdracht(en) | | ECTS | 10 | | Opmerkingen | Dit onderdeel maakt deel uit van de Erasmus Mundus Master "Language and Communication Technologies". |
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| 13 | Language and Culture | LTC017M03 |
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| Faculteit | Letteren | | Voertaal | Engels | | Docent(en) | | | ECTS | 3 |
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| 14 | Language, Brain and Cognition | LTR022M10 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. S.A. Sprenger | | Docent(en) | dr. S.A. Sprenger | | Onderwijsvorm | hoorcollege, werkcollege | | Toetsvorm | essay, presentatie, werkstuk(ken) | | ECTS | 10 | | Entreevoorwaarden | Dit vak is toegankelijk voor studenten van de Research Master. |
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| 15 | Language Development | LLS008M10 |
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| 16 | Language Modelling | WMCC003-05 |
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| Faculteit | Science and Engineering | | Voertaal | Engels | | Coordinator | dr. J.K. Spenader | | Docent(en) | dr. J.K. Spenader | | Onderwijsvorm | Hoorcollege (LC), Practisch werk (PRC) | | Toetsvorm | Opdracht (AST), Verslag (R) | | ECTS | 5 |
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| 17 | Language Technology Project | LIX025M05 |
| In this project-based course, students are going to work on a natural language processing challenge. A challenge is a practical task in NLP related to a particular research topic. The task usually comes with data-sets for training, as well as a precise evaluation metric. The intention is that students familiarize themselves with a selected research topic, implement a solution and present the outcome critically in a term paper. The course is a mix of lectures, exercises and project-based work. The focus of this class is on deep learning (neural networks) for NLP. |
| Faculteit | Letteren | | Voertaal | Engels | | Docent(en) | dr. A. Toral Ruiz | | Onderwijsvorm | werkcollege | | Toetsvorm | presentatie, werkstuk(ken) | | ECTS | 5 | | Entreevoorwaarden | BA exam Information Science or Artificial Intelligence or similar undergraduate programme.
Maturity in computational linguistics, meaning familiarity with basic concepts of computational linguistics and machine learning, but there will be time to review occasionally unfamiliar concepts as well. |
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| 18 | Learning from Data | LIX016M05 |
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| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | prof. dr. M. Nissim | | Docent(en) | prof. dr. M. Nissim | | Onderwijsvorm | hoorcollege, werkcollege | | Toetsvorm | computeropdrachten, verslag, wekelijkse opdrachten | | ECTS | 5 |
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| 19 | Linguistic Analysis | LTR026M10 |
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| 20 | LTABS | LTC020M06 |
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| 21 | Machine Learning | WMAI010-05 |
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| Faculteit | Science and Engineering | | Voertaal | Engels | | Coordinator | prof. dr. H. Jaeger | | Docent(en) | prof. dr. H. Jaeger | | Onderwijsvorm | Hoorcollege (LC), Practisch werk (PRC), Werkcollege (T) | | Toetsvorm | Verslag (R), Schriftelijk tentamen (WE) | | ECTS | 5 |
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| 22 | Methodology & Statistics Ling. Research | LTR002M10 |
This course is regularly attended by Research Master's students and PhD candidates and aims to enable participants to conduct statistical analyses of their data independently in R. The first half of the course follows on the first-semester course “Basic Statistics” and provides an introduction to multivariate statistics and visualization in R. Topics include one-way and factorial ANOVA, (multiple) regression, logistic regression, mixed-effects regression and generalized additive models. There are several R lab sessions in which these analyses are applied. The second half of the course revolves around seminar presentations (and practical sessions) by students on the use and application of various statistical statistical techniques or methodology in (their) research. See the following website for topics presented and discussed in 2004 through 2016: http://ww.let.rug.nl/nerbonne/teach/rema-stats-meth-seminar/.
Compulsory literature:- Harald Baayen (2008). Analyzing Linguistic Data. A Practical Introduction to Linguistics using R, Cambridge University Press: Cambridge. Available at http://www.sfs.uni-tuebingen.de/~hbaayen/publications/baayenCUPstats.pdf.
- Bodo Winter & Martijn Wieling (2016). How to analyze linguistic change using mixed models, Growth Curve Analysis and Generalized Additive Modeling. Journal of Language Evolution, 1(1): 7-18. Available at: https://academic.oup.com/jole/article/1/1/7/2281883/How-to-analyze-linguistic-change-using-mixed:
- Winter, Bodo (2013). Linear models and linear mixed effects models in R with linguistic applications. arXiv:1308.5499. Available at: https://arxiv.org/ftp/arxiv/papers/1308/1308.5499.pdf
- Martijn Wieling (2018). Generalized additive modeling to analyze dynamic phonetic data: a tutorial focusing on articulatory differences between L1 and L2 speakers of English. Journal of Phonetics, 70, 86-116. Available at: http://martijnwieling.nl/files/GAM-tutorial-Wieling.pdf
Optional literature:
Natalia Levshina (2015) How to do linguistics with R. Data exploration and statistical analysis John Banjamins: Amsterdam. |
| Faculteit | Letteren | | Voertaal | Engels | | Docent(en) | dr. A. Toral Ruizprof. dr. M.B. Wieling, MSc. | | Onderwijsvorm | computerpracticum, werkcollege | | Toetsvorm | presentatie, werkstuk(ken) | | ECTS | 10 | | Entreevoorwaarden | Participants in the course should have completed a basic course in statistics (e.g., Basic Statistics) covering topics such as descriptive statistics but also basic hypothesis testing using z-tests, t-tests, and chi-square. | | Opmerkingen | Open to others on permission of the instructor. |
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| 23 | Multichannel Management | LIX023M05 |
| Het college Multichannel Management introduceert verschillende theorieën die iets zeggen over kanaalkeuze, en wetenschappelijke studies die factoren aangeven die hierin een rol spelen. Het gaat vervolgens in op de vraag hoe theorieën over kanaalkeuze kunnen worden benut bij concrete vragen vanuit de maatschappij. Er is in dit college sprake van twee toepassingsgerichte foci. Een eerste toepassingsgerichte focus is de ‘multichannel management’ in de communicatie waarvoor overheidsinstanties in Nederland zich geplaatst zien, als er sprake is van een crisis. Sociale media nemen een belangrijke plaats in in deze media-mix. Sociale media beïnvloeden het werk van crisiscommunicatiedeskundigen. Burgers zijn nl. ook zelf actief op sociale media, bij crises. Overheidsinstanties zijn geïnteresseerd geraakt in de burgerbeleving na een crisis, en vragen zij zich af hoe ze deze het beste kunnen monitoren. Het monitoren van de burgerbeleving via sociale media vormt de tweede toepassingsgerichte focus van dit college. |
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| 24 | Natural Language Processing | LIX001M05 |
De cursus is een gevorderde cursus op het gebied van de natuurlijke taalverwerking. In de cursus wordt een aantal belangrijke, fundamentele, onderwerpen uit het vakgebied behandeld (Reguliere Expressies, Finite state automata, Computationele Morfologie, computationele fonologie, N-grams, Hidden Markov Models, Part-of-Speech Tagging, Context-free Grammar, Parsing, Unification Grammar,
Chomsky Hierarchy). |
| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. G. Bouma | | Docent(en) | dr. G. Bouma student-assistent | | Onderwijsvorm | computerpracticum, hoorcollege | | Toetsvorm | schriftelijk tentamen, schriftelijke opdracht(en) | | ECTS | 5 | | Entreevoorwaarden | Bachelor Informatiekunde of bachelor Kunstmatige Intelligentie of vergelijkbare opleiding op bachelor-niveau. | | Opmerkingen | De student Informatiekunde kiest twee van de volgende vier mogelijkheden: Natural Language Processing; Advanced Webtechnology; Computer-Mediated Communication; Machinaal Leren plus een Ma-keuzeonderdeel van buiten de opleiding. Studenten Informatiekunde die het vak Machinaal Leren willen kiezen moeten van tevoren contact opnemen met de studieadviseur. |
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| 25 | Neuroimaging and Language | LTC016M05 |
The focus of this module is the relationship between Event Related Potentials (ERPs) as a neuroimaging technique and real time language processing. The course consists of lectures and practical sessions.
The lectures are dedicated to theoretical issues regarding both language processing and methodological/technical aspects of ERP research. In the practical sessions the students will gain hands-on experience in creating and conducting an ERP experiment. They will also learn to analyze and interpret data. |
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| 26 | ReMa Internship Linguistics EMCL | LTC000M10 |
By doing a research internship, students learn to conduct independent
neurolinguistic or clinical linguistic research. Students gain experience, under
supervision, in applying specific methods and techniques for neurolinguistic
and clinical linguistic research, and are involved in a research project.
Typically there are two types of research internships, or a combination of
both. A) Students complete a small research project in collaboration with the
internship supervisor. Tasks may include: reviewing the relevant literature,
designing an experiment, developing materials, collecting and analysing data,
presenting results, writing a research report. B) Students participate in daily
lab activities and/or learn special research techniques or analyses. In this
case there is no small, dedicated project that is run by the intern. It is possible
that an internship leads to a joint presentation of student and supervisor(s)
at a national or international conference. Some studies may result in an
article in a conference proceedings or journal. Occasionally students decide
to connect their subsequent MA thesis to the research that was done during
the internship, by extending the scope of investigation. |
| Faculteit | Letteren | | Voertaal | Engels | | Docent(en) | | | Onderwijsvorm | stage | | Toetsvorm | presentatie, stageverslag | | ECTS | 10 |
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| 27 | ReMa Thesis Linguistics: EMCL | LTC999M30 |
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| 28 | Research Master's Internship Linguistics | LTR000M25 |
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| 29 | Research Training 1 | LTR028M05 |
The aim of this module is to provide the opportunity for students to work under the supervision of an experienced researcher and contribute to the researcher’s project. The goal is for students to get hands-on experience in data collection and data analysis in any or all of its phases. Students may do this module for 5 or 10 ETCS; it is available in every semester.
What it entails: This module may include completing readings or compiling a bibliography, but may not focus solely on a literature review. While it will almost certainly be necessary for the student to gain background knowledge through reading specific texts, the goal of this module is for students to learn to carry out research using a particular methodology and approach to linguistic analysis in the context of the supervisor’s research program.
Not just a research assistant: While this module is intended to also benefit scholars in our faculty, the primary goal is not to provide research assistants to faculty members but to provide research experience to students. Although the student need not participate in all phases of the research, situating the research process in the larger context of theory is a requirement of the experience provided for the student. Students will be evaluated on their work on the project and also a short essay and discussion of the research which illustrates their understanding of the research in terms of its contribution to the field.
Process:
Information about research projects are posted on the ReMa Nestor page; you can find these in a folder labelled ‘Research Training’ on the ‘Content’ tab.
(You may also work with other research supervisors who have not submitted descriptions, if you know a staff member who is doing a project you would be interested in; the point of these project descriptions is simply to improve information flow, not to limit who can supervise research training.)
If you find a project you would like to participate in, contact the supervisor directly to work out the details. Please complete the Research Training form in consultation with the research supervisor, including both of your signatures. Please email this completed form to Nadja Zadorina, the Research Master coordinator, who will enroll you in the module. |
| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | prof. dr. J.M. Fuller | | Docent(en) | | | Onderwijsvorm | tutorial | | Toetsvorm | nog niet bekend | | ECTS | 10 |
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| 30 | Research Training 2 | LTR029M05 |
The aim of this module is to provide the opportunity for students to work under the supervision of an experienced researcher and contribute to the researcher’s project. The goal is for students to get hands-on experience in data collection and data analysis in any or all of its phases. Students may do this module for 5 or 10 ETCS; it is available in every semester.
What it entails: This module may include completing readings or compiling a bibliography, but may not focus solely on a literature review. While it will almost certainly be necessary for the student to gain background knowledge through reading specific texts, the goal of this module is for students to learn to carry out research using a particular methodology and approach to linguistic analysis in the context of the supervisor’s research program.
Not just a research assistant: While this module is intended to also benefit scholars in our faculty, the primary goal is not to provide research assistants to faculty members but to provide research experience to students. Although the student need not participate in all phases of the research, situating the research process in the larger context of theory is a requirement of the experience provided for the student. Students will be evaluated on their work on the project and also a short essay and discussion of the research which illustrates their understanding of the research in terms of its contribution to the field.
Process:
Information about research projects are posted on the ReMa Nestor page; you can find these in a folder labelled ‘Research Training’ on the ‘Content’ tab.
(You may also work with other research supervisors who have not submitted descriptions, if you know a staff member who is doing a project you would be interested in; the point of these project descriptions is simply to improve information flow, not to limit who can supervise research training.)
If you find a project you would like to participate in, contact the supervisor directly to work out the details. Please complete the Research Training form in consultation with the research supervisor, including both of your signatures. Please email this completed form to Nadja Zadorina, the Research Master coordinator, who will enroll you in the module. |
| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | prof. dr. J.M. Fuller | | Docent(en) | | | Onderwijsvorm | tutorial | | Toetsvorm | nog niet bekend | | ECTS | 5 |
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| 31 | ResMa Thesis Linguistics, Thesis Class | LTR999M30 |
| Studenten rapporteren over hun onderzoek in de vorm van een MA-scriptie. De scriptie moet geschikt zijn voor publicatie in een wetenschappelijk tijdschrift. De scriptie wordt individueel begeleid door een docent. Studenten dienen ook een scriptieklas bij te wonen waarin de voortgang van hun scriptie in de gaten wordt gehouden en de mogelijkheden van een promotietraject of andere beroepsperspectieven worden besproken. Zie het scriptiereglement voor de eisen die aan een scriptie worden gesteld. |
| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. S.A. Sprenger | | Docent(en) | dr. S.A. Sprenger | | Onderwijsvorm | zelfstudie (begeleid) | | Toetsvorm | scriptie | | ECTS | 30 | | Entreevoorwaarden | Voltooiing modules Basic Statistics, Corpus Analysis, Linguistic Theory |
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| 32 | Semantic Web Technology | LIX002M05 |
In het eerste deel van de cursus wordt de motivatie voor het ontwikkelen van een "semantisch web" besproken, en worden verschillende XML-standaards en technieken voor het semantisch web behandeld. We gaan met name in op het gebruik van de Protégé Ontology editor, RDF, OWL and SPARQL.
In het tweede deel van het college wordt in projectvorm een applicatie ontwikkeld op het gebied van de Letteren, die gebruik maakt van deze technieken. |
| Faculteit | Letteren | | Voertaal | Engels | | Coordinator | dr. G. Bouma | | Docent(en) | dr. G. Bouma | | Onderwijsvorm | computerpracticum, hoorcollege | | Toetsvorm | computeropdrachten, essay, referaat/spreekbeurt | | ECTS | 5 | | Entreevoorwaarden | Bachelor Informatiekunde of bachelor Kunstmatige Intelligentie of vergelijkbare opleiding op bachelor-niveau. |
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| 33 | Seminar/Summerschool/Winterschool 1 | LTR015M05 |
| De student neemt actief deel aan een module van de Landelijke Onderzoekschool Taalwetenschap LOT. Naar aanleiding van deze module schrijft de student een onderzoeksverslag. |
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| 34 | Seminar/Summerschool/Winterschool 2 | LTR016M05 |
| De student neemt actief deel aan een module van de Landelijke Onderzoekschool Taalwetenschap LOT. Naar aanleiding van deze module schrijft de student een onderzoeksverslag. |
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| 35 | Web and Cloud Computing | WMCS005-05 |
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| 36 | Writing: Context, Process and Text | LLS025M10 |
In this course writing will be looked at from different theoretical perspectives. Sociocultural, cognitive and linguistic approaches to the study of writing contexts, writing processes and texts will be discussed. Lectures, presentations and discussions will introduce the participants into theories, methods and current issues in writing research. In a series of practicals students will get acquainted with tools and technologies for the elicitation, registration and analysis of writing data. Students will conclude the course with a small-scale empirical study. The tentative syllabus of the course is outlined below.
Topics for lectures and presentations include: theoretical approaches to writing, writing in the real world, cognitive and psycholinguistic models of writing, connections between writing, speaking and reading, technologies for writing, writing development, multilingual writing, writing education, characteristics of writers, and assessing writing. Topics for practicals include ethnography of writing, think-aloud protocols, key-stroke logging, revision analysis, text analysis, questionnaires, and assessment techniques. |
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