Modules CALM
Digital Communication Management
Having a solid background in digital communication and marketing is a key asset for language professionals. This course offers such a background by digging deeper into the three digital media types -owned, earned and paid media- and zooms in on topics such as digital marketing, search engine optimization, social media campaigning and web analytics. Students will not only study these topics in close detail, but they will also learn how to conceptualize and implement a social media and digital marketing campaign.
Digital Public Relations
prepares students to become professionals in today’s communication industry by introducing them to the most important topics regarding digital public relations. Students acquire both the knowledge and skills to strategically manage relationships with internal and external stakeholders. This course covers topics such as employee social media use, employee brand ambassadorship, authenticity on social media, the importance of dialogue and crisis communication.
Technical Writing
covers the basics of technical communication. In hands-on sessions, students learn how to write technical documentation using the principles of clear, concise, and consistent writing while keeping the audience in mind. Students work with software used by professional technical writers, giving them a head start on the job market.
Desktop Publishing
introduces students into the layout and page design software Adobe InDesign. Students acquire a solid background in color manage- ment, offset and digital printing and layout principles for magazine, business card, photo book and package design. The sessions are interactive and hands-on to allow students to maximize their experience with creating print and digital media. DTP skills are particularly relevant for language professionals who need to produce copy or translations directly in the target format to better match the text to the layout and to reduce production time.
Machine Translation and Post-Editing
is a comprehensive course in which students first acquire a solid theoretical background. Different types of machine translation architectures and evaluation methods are discussed. The course also focuses on how machine translation can be integrated in a high- quality human translation production process. In hands-on sessions students learn to build their own customized MT system and learn to identify and tackle the typical post-editing challenges.
Terminology and Translation Technology
covers the fundamental principles of the theory of terminology and terminology management and familiarizes students with computer-based aids for translation, especially terminology extraction, terminology management and translation memory tools.
Localisation
refers to the cultural adaptation and translation of digital content. The course covers the main concepts and technical aspects of localisation. Students learn to localise different sources of digital contents (software applications, including user interfaces and online help files, websites, games and e-learning content).
Audiovisual Language Techniques
introduces students into the techniques required for different modes of audiovisual translation that increase access to various types of cultural content.
In hands-on sessions, students learn how to produce intralingual and interlingual subtitles with professional software and to create audio descriptions. Furthermore, the course discusses recent technologies and scientific research that drive the automation of the field.
Natural Language Processing
covers the fundamentals of Natural Language Processing (NLP). By diving deeper into statistical techniques to analyze text, both at the syntactic and the semantic level, students will acquire insights into state-of-the-art methods to model language from a computational perspective. Several techniques (information extraction, machine learning, deep learning) are discussed to approach a wide variety of problems and applications, including sentiment analysis and emotion detection, event extraction, machine translation, and more.
Introduction to Language Processing with Phyton
offers an introduction to programming, focusing on automatic text processing. This course does not require prior knowledge of programming. Python is a popular programming language for natural language processing (NLP).
Advanced Language Processing with Phyton
builds further on the introductory course and students will make use of NLP libraries to tackle NLP problems using super- vised machine learning techniques, such as linear and logistic regression, and to evaluate and visualize the performance of machine learning models.
Computer-Assisted Language Learning
is a comprehensive course in which students acquire a strong background in Computer-assisted Language Learning (CALL). Recent technologies and findings are discussed such as Web 2.0, mobile-assisted language learning, gamification, (L)MOOCS and intelligent CALL. Large parts of the course are devoted to get to know and critically access a variety of electronic CALL applications zooming in on various language skills (reading, writing, speaking, listening,...).