Courses

Module 1: Introduction to statistics with R

This module offers a basic and practical introduction to statistical data analysis for (applied) linguistics and translation and interpreting studies. Each lesson consists of a theoretical introduction followed by practical hands-on exercises with R.
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Module 2: Advanced statistical methods with R

This course offers an introduction to categorical data analysis which is specifically geared towards researchers in the field of (variational) linguistics and empirical translation studies.
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Module 3: Natural Language Processing with Python

Natural Language Processing or NLP is a discipline that focuses on the interaction between data science and human language and gives the machines the ability to read, understand and derive meaning from human languages. The participants of this course will learn about different NLP techniques and basic programming skills.
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Module 4: PRAAT

This course will introduce Praat scripting. By using scripts it will be much easier to replicate your analyses on speech files and to communicate with others about what you have done and how you have done it.
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Module 5: ELAN

This is an introductory course to the use of ELAN (EUDICO Linguistic Annotator), an annotation tool for video’s and sound recordings.
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Module 6: Eye-tracking

Over the last decades, eye tracking has become a wide-spread technique to understand how people process and learn language. In this course, we will cover a basic introduction to eye-tracking techniques in language science.
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Module 7: Survey design

This course aims to introduce the essential steps in survey research, from setting up the process of data collection to basic statistical analysis.
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Module 8: Linguistic ethnography

Qualitative research is an iterative process. In this course, participants will be introduced to the basic ideas behind qualitative ethnographic research methods in the context of linguistics, focussing on the ingredients required for this process, i.e. data collection and analysis.
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Module 9: Introduction to linear mixed modelling

This course covers some important ideas relating to linear mixed models and how they can be used in language research. We will loosely follow the textbook draft:  https://vasishth.github.io/Freq_CogSci/.

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