Master of Science in Computational Linguistics and Language Technology [MSc(CLLT)] [*Subject to University’s Approval] | Academy for Applied Policy Studies and Education Futures

Programme Code

One-Year Full-time / A1M164

Two-Year Part-time / C2M075*

Programme Leader

Professor Gu Mingyue Michelle (Co-Programme Leader)

Professor Glenn Stockwell (Co-Programme Leader)

Enquiry (Admission)

acadmission@eduhk.hk

Enquiry (Programme)

msccllt@eduhk.hk

Introduction

The Master of Science in Computational Linguistics and Language Technology [MSc(CLLT)] programme is established against the background of artificial intelligence (AI) and technology innovation, when language models have brought machines a significant step closer to understanding human language and generating human-like responses. This programme is strategically designed to cultivate a future generation of talents and practitioners to explore the fast-evolving field of computational linguistics at the intersection of linguistics and computer science. The curriculum offers courses that equip students from computer science, AI, or engineering backgrounds with in-depth knowledge and required skills in the study of language, linguistics, and social sciences.

This programme will prepare its graduates to work in different industries such as software development related to language and translation, language education, and entrepreneurship in language technology in the Greater Bay Area (GBA) and beyond. They could become leaders and informed decision-makers capable of driving sustainable and inclusive digital transformation in the GBA, and beyond.

* For information on whether a non-local student can study a full-time or part-time programme, please refer to Taught Postgraduate Programmes - FAQs webpage.

According to the Education Bureau (EDB), definition of local and non-local applicants is as listed here.

To make direct enquiries on the definition of non-local students, please contact EDB (Email: edbinfo@edb.gov.hk / Fax: (852) 2804 6499).

Programme Highlights

The FIRST dedicated Master's Programme in Computational Linguistics in Hong Kong.
Interdisciplinary Training in Linguistics + Computer Science.
Dual Focus on Language Technology and AI Applications.
Supporting Language Tech Entrepreneurship and Employment in the Greater Bay Area.
Driving Leadership in Sustainable and Inclusive Digital Transformation.

Disclaimer

The University is committed to upholding the educational quality and standard of the programmes it offers. The University, being funded by the University Grants Committee (UGC), is one of the nine self-accrediting institutions in Hong Kong. In addition, the quality of the educational experience in all programmes offered by the UGC-funded universities is subject to the quality assurance process administered by the Quality Assurance Council of the UGC. Individuals who wish to apply for qualification certification in Chinese Mainland after graduation should contact the CSCSE (website: https://zwfw.cscse.edu.cn/cscse/lxfwzxwsfwdt2020/xlxwrz32/index.html) directly for updated details and confirmation. The certification in Chinese Mainland is an independent process from the conferral of academic qualification in Hong Kong by the University. For the avoidance of doubt, no warranties are given in respect of individual graduate’s qualification certification or recognition in Chinese Mainland or any other professional qualification or license outside Hong Kong.

In the event of inconsistency between information in English and Chinese versions or where an interpretation of the programme content is required, the decision of the University shall be final.

Every effort has been made to ensure the accuracy of the information contained in this website. Changes to any aspects of the programmes may be made from time to time as due to change of circumstances and the University reserves the right to revise any information contained in this website as it deems fit without prior notice. The University accepts no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.

Any aspect of the courses and course offerings (including, without limitation, the contents of the course and the manner in which the course is taught) may be subject to change at any time at the sole discretion of the University if necessary. Without limiting the generality of the University’s discretion to revise the courses and course offerings, it is envisaged that changes may be required due to factors including staffing, enrolment levels, logistical arrangements, curriculum changes, and other factors caused by change of circumstances. Tuition fees, once paid, are non-refundable.

EdUHK, has not collaborated with any agency in Chinese Mainland or Hong Kong on admission, and does not encourage students to entrust their applications to any third-party agents and we always contact applicants directly on updates regarding the applications. You must complete and submit your own application via the EdUHK online admissions system and provide your own personal and contact details. Please refer to the official EdUHK channels, such as programme websites and the admissions system, for the required information to complete your application.

Important Notes for Students from Chinese Mainland on Overseas Credential Evaluation (國(境)外學歷學位認證)

Students who have fulfilled the programme requirements will be conferred the degree upon the approval of the University's Academic Board. The University bears no responsibility for the evaluation of its degrees outside of Hong Kong. Students are advised to consult with the relevant authority(ies) for the prevailing rules/regulations.

Individuals who would seek qualification certification in Chinese Mainland after graduation should contact the Chinese Service Centre for Scholarly Exchange (CSCSE) 中國(教育部) 留學服務中心 (https://www.cscse.edu.cn) for updated details.

The certification in Chinese Mainland is an independent process from the conferral of academic qualification in Hong Kong by the University. For the avoidance of doubt, no warranties are given in respect of individual graduate's qualification certification or recognition in Chinese Mainland or any other professional qualification or license outside Hong Kong.

CSCSE takes a very prudent approach in evaluating each application, including the students' residential period in Hong Kong during the entire study period. When evaluating graduates' credentials, the full border entry and exit records of individual applicants will be examined.

Students who would pursue credential recognition should be aware that short stays in Hong Kong during the study period may not fulfil the CSCSE residential requirements, leading to possible uncertainty and risks to their credential recognition.

Students are seriously advised to consider the above when making personal plans, such as accommodation and travel plans from Hong Kong, etc. and make necessary arrangements where appropriate.

It is the responsibility of the students to be familiar with and comply with the University regulations and guidelines governing the Taught Postgraduate Programmes. Students should refer to the Graduate School website for the General Academic Regulations and the Code of Practice for Taught Postgraduate Programmes for details.

Students should consult with CSCSE if they have any enquiries.

1 June 2025

Programme Aims

To provide students with a robust and integrative foundation in the core theories of linguistics (e.g., phonetics, phonology, morphology, syntax, semantics, pragmatics, language acquisition, psycholinguistics) and their interaction with computer sciences (e.g., natural language processing, machine learning, deep learning), enabling them to understand theories, models, computational research methods, and knowledge in the related fields.
To equip students with the ability to translate computational linguistics theories into real-world applications and solutions across diverse industries related to language technology, fostering innovations that contribute to the development of society.
To integrate computational models and AI into applied linguistics and language education, equipping educators, developers, and language practitioners with cutting-edge methodologies to drive innovation in language technology.
To cultivate researchers capable of conducting original research and interdisciplinary studies that bridge computational methods with cognitive science, education, and data science.

Prospective Students

The ideal prospective student pool includes local and non-local degree holders seeking specialized interdisciplinary training in linguistics and computer science.

Programme Structure

The programme comprises 30 credit points(cps), including 6 core courses (18 cps) and 4 elective courses (select 4 out of 6 courses, 12 cps) or 2 elective courses and a capstone project (12 cps in total). Each course carries 3 cps or 6 cps.

Core courses	18 cps
Elective courses	12 cps
Total	30 cps

Programme Curriculum

Type	Course Title	Credit Points (cps)
Core course	Foundations of Computational Linguistics	3
Core course	Linguistic Foundations for Natural Language Processing	3
Core course	Computational Corpus Linguistics and Text Mining	3
Core course	AI & Technologies in Language Learning and Teaching	3
Core course	Natural Language Processing Applications	3
Core course	Data Analytics in Linguistics	3
Elective course	Linguistic Analysis of Large Language Models	3
Elective course	Machine Learning for Natural Language Processing	3
Elective course	Deep Learning for Natural Language Processing	3
Elective course	Multilingual and Low-Resource Natural Language Processing	3
Elective course	Computational Semantics	3
Elective course	Knowledge Representation in Language Technologies	3
Capstone project	Capstone Project in Computational Linguistics and Language Technology	6

Course Details

Core Courses

Foundations of Computational Linguistics

This course introduces computational linguistics as a field at the intersection of language and computation. It examines how insights from linguistics inform computational approaches to language, and how computational models can be used to investigate language data and support natural language processing tasks. Students are introduced to major approaches in the field, including symbolic, probabilistic, and neural methods, alongside a discussion of contemporary applications and emerging issues in language technologies.

Linguistic Foundations for Natural Language Processing

This course introduces core concepts in linguistic analysis that underpin natural language processing. Drawing on phonetics, phonology, morphology, syntax, semantics, and pragmatics, the course connects linguistic theory with computational approaches to language. Students explore applications to tasks such as speech processing, parsing, meaning representation, and language understanding across diverse languages and communicative contexts.

Computational Corpus Linguistics and Text Mining

This course examines computational approaches to linguistic corpora in text mining, contemporary computational linguistics, and natural language processing. Students explore how computational engagement with language data informs language analysis and computational modelling, and how corpus evidence contributes to language technologies operating across multilingual and socially situated contexts.

AI & Technologies in Language Learning and Teaching

In line with the evolution and use of Artificial Intelligence tools in applied linguistic studies, this course introduces the application of computer-assisted language learning (CALL), mobile-assisted language learning (MALL), gamification, and corpus linguistics in language learning and teaching. This course examines issues such as learner engagement, autonomy, task design, and the affective and contextual factors that shape technology use, bridging theory and practice.

Natural Language Processing Applications

This course examines the use of natural language processing in contemporary language technologies and real-world contexts. Drawing on case studies, datasets, industry applications, and project work, students explore practical applications of NLP in areas such as communication, multilingual interaction, machine translation, language learning, and large-scale text analysis. The course also considers the opportunities and challenges that arise when NLP is applied across different domains, user groups, and linguistic settings.

Data Analytics in Linguistics

This course introduces students to basic theories and methods of data analytics used in linguistics, covering topics from effective ways of interpreting, visualising and presenting quantitative data related to linguistic analysis, to statistical and computational methods, including machine learning, natural language processing, and predictive modelling, to extract meaningful insights from complex linguistics datasets. Students will also explore related tools for interpreting quantitative linguistic data and the basic technologies for such analysis. Students will also explore specific linguistic features (e.g., morphological and syntactic analysis, semantics representation) and processing.

Elective Courses

Linguistic Analysis of Large Language Models

This course examines large language models (LLMs) from linguistic and computational perspectives. Students explore what contemporary language models reveal about language, meaning, and communication across different languages and contexts. Drawing on ideas from linguistics, NLP, and cognitive research, the course considers approaches to interpreting and evaluating model behaviour and their significance for contemporary language technologies.

Machine Learning for Natural Language Processing

This course introduces machine learning approaches for analysing and modelling language data. Students engage with core techniques used in contemporary NLP, including classification, sequence modelling, language representation, and model evaluation. The course explores applications ranging from text analysis and information extraction to conversational AI. Practical activities provide experience working with NLP datasets, computational tools, and real-world language problems.

Deep Learning for Natural Language Processing

This course examines deep learning methods used in contemporary NLP. Topics include language models, attention mechanisms, transformers, and recent developments in large language models. Students explore their use in tasks such as text generation, dialogue systems, question answering, and machine translation, together with current research, model limitations, and ongoing challenges in understanding and evaluating deep learning approaches to language.

Multilingual and Low-Resource Natural Language Processing

This course examines natural language processing in multilingual, under-resourced, and data-constrained language settings. It explores the challenges of building and evaluating NLP systems when language data are unevenly distributed or shaped by linguistic and cultural variation. Students consider methods for multilingual communication, cross-lingual transfer, and the development of language technologies beyond high resource contexts.

Computational Semantics

Computational systems can process linguistic form without necessarily capturing the meanings conveyed through language. The course explores computational approaches to natural language meaning and considers how semantic analysis informs contemporary NLP and language technologies. Using examples from language technologies, students explore the role of meaning representation in language understanding and computational models of language.

Knowledge Representation in Language Technologies

Language technologies rely on computational representations of meaning and knowledge. The course explores the relationship between human language and computational systems, focusing on the challenges of representing knowledge computationally and the aspects of communication that may resist formalisation. Using case studies from contemporary language technologies, students consider the assumptions and consequences involved in relating human communication to computational forms of knowledge.

Capstone Project in Computational Linguistics and Language Technology

This capstone project is a practice oriented enquiry that bridges computational linguistics theories with real world language technology applications. Students will independently define a concrete problem, design a feasible solution—typically a working prototype, a system evaluation, or a data driven analysis—and implement it using appropriate NLP tools and frameworks. The project emphasises the entire practical workflow: from data collection and preprocessing, to model building or system integration, to performance assessment using meaningful metrics and consideration of deployment constraints such as scalability, efficiency, and user experience. Students are encouraged to draw on authentic datasets and, where possible, align their work with industry or community needs. The final submission comprises a concise project report and an oral demonstration, highlighting both technical skills and the ability to communicate outcomes clearly.

Medium of Instruction

Chinese (mainly Putonghua)

Study Location

Classes in the same or different semester(s) may be scheduled on weekday daytime/evenings, weekends and/or during long holidays at the Tai Po Campus / Tseung Kwan O Study Centre / North Point Study Centre / West Kowloon Study Centre / Kowloon Tong Satellite Study Centre and/or other locations as decided by the University. The final choice of study location is subject to the University's discretion.

Career Prospects

Language Technology Industry: Natural Language Processing (NLP) Engineers, Language Model Developers, Machine Translation Specialists
EdTech Sector: AI Education Product Designers, Intelligent Language Learning System Developers
Academic Research: Pursuing PhD studies in Computational Linguistics, Natural Language Processing, Artificial Intelligence, and related fields
Government & Public Sector: Digital Transformation Strategists, Language Resource Planners
Innovation & Entrepreneurship: Language Technology Ventures in the Greater Bay Area (GBA)

Teaching Team

Co-Programme Leader	Professor Gu Mingyue Michelle	mygu@eduhk.hk
Co-Programme Leader	Professor Glenn Stockwell	gstock@eduhk.hk
Professor	Professor Ma Qing Angel	maqing@eduhk.hk
Assistant Professor	Dr Lau Chaak Ming	lchaakming@eduhk.hk
Research Assistant Professor	Dr Zhang Shuting	zshuting@eduhk.hk

Additional academic staff specialising in Computational Linguistics will join the team soon.

Disclaimer

In the event of inconsistency between information in English and Chinese versions or where an interpretation of the programme content is required, the decision of the University shall be final.

Important Notes for Students from Chinese Mainland on Overseas Credential Evaluation (國(境)外學歷學位認證)

Students who have fulfilled the programme requirements will be conferred the degree upon the approval of the University's Academic Board. The University bears no responsibility for the evaluation of its degrees outside of Hong Kong. Students are advised to consult with the relevant authority(ies) for the prevailing rules/regulations.

Individuals who would seek qualification certification in Chinese Mainland after graduation should contact the Chinese Service Centre for Scholarly Exchange (CSCSE) 中國(教育部) 留學服務中心 (https://www.cscse.edu.cn) for updated details.

The certification in Chinese Mainland is an independent process from the conferral of academic qualification in Hong Kong by the University. For the avoidance of doubt, no warranties are given in respect of individual graduate's qualification certification or recognition in Chinese Mainland or any other professional qualification or license outside Hong Kong.

CSCSE takes a very prudent approach in evaluating each application, including the students' residential period in Hong Kong during the entire study period. When evaluating graduates' credentials, the full border entry and exit records of individual applicants will be examined.

Students who would pursue credential recognition should be aware that short stays in Hong Kong during the study period may not fulfil the CSCSE residential requirements, leading to possible uncertainty and risks to their credential recognition.

Students are seriously advised to consider the above when making personal plans, such as accommodation and travel plans from Hong Kong, etc. and make necessary arrangements where appropriate.

It is the responsibility of the students to be familiar with and comply with the University regulations and guidelines governing the Taught Postgraduate Programmes. Students should refer to the Graduate School website for the General Academic Regulations and the Code of Practice for Taught Postgraduate Programmes for details.

Students should consult with CSCSE if they have any enquiries.

1 June 2025

Entrance Requirements (for 2027/28 Admission)

1. General Requirements

Applicants should normally hold a recognised Bachelor’s degree or equivalent qualifications, preferably in one of the following areas: linguistics, language science and technology, computer science, AI, engineering, and other related fields. Relevant work experience is preferred.
For applicants without a background in computer programming, completion of the non-credit-bearing "Summer Bootcamp in Coding & Programming for Computational Linguistics" serves as a conditional requirement for admission. (Please note that enrolment in or completion of the bootcamp is a conditional requirement and does NOT guarantee final admission to the programme if the applicant fails to meet other relevant admission criteria. This bootcamp requires an extra fee in addition to regular programme tuition.)
Applicants who obtained degrees from universities in Chinese Mainland are required to provide:
- Degree Certificate（學位證書-中文原件掃描）and Online Verification Report of Higher Education Degree Certificate（學位在線驗證報告）issued by the CHSI （學信網）with a validity period of six months;
- Graduation Certificate（畢業證書-中文原件掃描）and Online Verification Report of Higher Education Qualification Certificate（學歷證書電子註冊備案表）issued by the CHSI（學信網）with a validity period of six months; and
- Final Transcript（最終成績單-中文原件掃描）.

2. Work Experience

Relevant work experience in linguistics, language science and technology, computer science, AI, engineering, and other related fields is preferred.

3. Chinese Language Proficiency Requirements

As the medium of instruction is primarily Mandarin, applicants need good Chinese language proficiency to complete the programme.

4. Interview

Applicants may be required to attend an admission interview.

5. Supplementary Documents

Applicants should submit a statement of purpose in English or Chinese (no more than 1,000 words/Chinese characters) outlining their career goals and interest in the programme.

Tuition Fee

HKD210,000 (30 cps)

The tuition fee is provisional and subject to adjustment. Tuition fees paid are normally not refundable or transferable. Students who still need to take courses to meet graduation requirements beyond the regular study period will need to pay a fee for extended study.

AAPSEF Entrance Scholarship

Starting from the 2026/27 academic year, the Academy for Applied Policy Studies and Education Futures will offer a one-off entrance scholarship (HK$30,000) to local and non-local students with outstanding academic and non-academic achievements in its taught postgraduate programmes.

Places are limited. Please visit the Academy’s website for details.

Application and Enquiries

Admission: acadmission@eduhk.hk

Programme: msccllt@eduhk.hk

Interested applicants should submit their applications via EdUHK Online Application Systems. Prior to submission, please visit https://www.eduhk.hk/acadprog/postgrad/index.html for detailed application and admission information.

Disclaimer

In the event of inconsistency between information in English and Chinese versions or where an interpretation of the programme content is required, the decision of the University shall be final.

Important Notes for Students from Chinese Mainland on Overseas Credential Evaluation (國(境)外學歷學位認證)

Students who have fulfilled the programme requirements will be conferred the degree upon the approval of the University's Academic Board. The University bears no responsibility for the evaluation of its degrees outside of Hong Kong. Students are advised to consult with the relevant authority(ies) for the prevailing rules/regulations.

Individuals who would seek qualification certification in Chinese Mainland after graduation should contact the Chinese Service Centre for Scholarly Exchange (CSCSE) 中國(教育部) 留學服務中心 (https://www.cscse.edu.cn) for updated details.

The certification in Chinese Mainland is an independent process from the conferral of academic qualification in Hong Kong by the University. For the avoidance of doubt, no warranties are given in respect of individual graduate's qualification certification or recognition in Chinese Mainland or any other professional qualification or license outside Hong Kong.

CSCSE takes a very prudent approach in evaluating each application, including the students' residential period in Hong Kong during the entire study period. When evaluating graduates' credentials, the full border entry and exit records of individual applicants will be examined.

Students who would pursue credential recognition should be aware that short stays in Hong Kong during the study period may not fulfil the CSCSE residential requirements, leading to possible uncertainty and risks to their credential recognition.

Students are seriously advised to consider the above when making personal plans, such as accommodation and travel plans from Hong Kong, etc. and make necessary arrangements where appropriate.

It is the responsibility of the students to be familiar with and comply with the University regulations and guidelines governing the Taught Postgraduate Programmes. Students should refer to the Graduate School website for the General Academic Regulations and the Code of Practice for Taught Postgraduate Programmes for details.

Students should consult with CSCSE if they have any enquiries.

1 June 2025