Charles University Faculty of Mathematics and Physics
Master in Computer Science - Language Technologies and Computational Linguistics
Prague, Czech Republic
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
STUDY FORMAT
On-Campus
Key Summary
About: The Master in Computer Science (Language Technologies and Computational Linguistics) trains students for research and application in natural language processing of written and spoken language. It covers mathematical and algorithmic foundations and methods in statistics and machine learning. Students may focus on language description or technology-oriented language data processing. Programs run in English and follow a two-year master's structure.
Career Outcomes: Graduates build systems for information retrieval, information extraction, summarization, question answering, machine translation, speech processing, and dialogue systems. They gain software development, teamwork, and machine learning skills for research roles, industry R&D, and engineering positions in language technology.
The aim of the study program “Computer Science – Language Technologies and Computational Linguistics” is to get the graduates ready for research in the area of natural language processing and the development of applications dealing with both written and spoken language. Examples of such applications are systems of information retrieval, information extraction and summarization, machine translation, text analytics, grammar checking, automatic speech recognition, spoken dialogue systems, and speech synthesis. The emphasis is put on a deep understanding of formal mathematical and algorithmic foundations and their practical applicability in natural language processing tasks. Students of the program have the possibility to focus either on theoretical aspects of formal description of natural languages or on the technology-oriented side (state-of-the-art methods in statistics, machine learning, and deep learning) for language data processing.
The graduate is familiar with mathematical and algorithmic foundations of automatic natural language processing, with theoretical foundations of formal description of natural languages, as well as with state-of-the-art machine learning techniques. Graduates have the ability to apply the knowledge acquired during their studies in the design and development of systems automatically processing natural language and large quantities of both structured and unstructured data, such as information retrieval, question answering, summarization and information extraction, machine translation, and speech processing. They are equipped with good knowledge, skills, and experience in software development and teamwork applicable in all areas involving the development of applications aiding human-computer interaction and/or machine learning.
