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Computational Linguistics PGDip (Online)

Understand the impact of AI-powered language technologies

100% Online

15 months (part-time)

120 credits

4 starts per year

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Develop advanced skills in Computational Linguistics

Goldsmiths, University of London’s online Postgraduate Diploma (PGDip) in Computational Linguistics is designed for learners who want to understand the technologies behind large language models and conversational AI without committing to a full master’s degree. Built around three core principles—linguistic awareness, technical literacy, and social responsibility—the programme combines linguistics, natural language processing, and machine learning to help you design and evaluate human-centered language technologies. You’ll graduate with advanced skills to contribute confidently to the rapidly evolving field of AI.

Programme benefits

  • Gain interdisciplinary skills beyond core computing
  • Examine the ethical and societal impact of AI
  • Build expertise in NLP, conversational AI, and large language models
  • Develop practical, career-focused skills
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A curriculum that combines linguistic and technical skills

8 courses

120 credits

The curriculum is built around practical, project‑based learning, enabling you to develop both technical expertise and critical awareness of the social and ethical implications of language technologies.

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Core Computational Linguistics PGDip modules

Exploring the fundamental principles of linguistic analysis, this module develops students’ understanding of how language is structured and how meaning is created and interpreted. Students will examine key levels of linguistic organisation, including phonology, morphology, syntax, semantics, and pragmatics, applying theoretical frameworks to the analysis of authentic language data. The module investigates how grammatical structures encode meaning, how context shapes interpretation, and how language varies across social and communicative settings. Through critical engagement with linguistic theories and methods, students will develop the analytical skills required to investigate language systematically and independently, providing a foundation for further study of language in applied, computational, and interdisciplinary contexts.
Developing practical programming skills for language and data analysis, this module introduces students to the tools and techniques required to acquire, process, and explore data using Python. Students will learn how to collect, clean, validate, and manipulate datasets through structured and reproducible workflows, applying programming concepts to real analytical challenges. The module emphasises the use of data structures, libraries, and visualisation techniques to support exploratory analysis and evidence-based reasoning. Through hands-on engagement with data, students will develop the technical competence and critical awareness required to conduct responsible data analysis and prepare for advanced study in machine learning, natural language processing, and computational linguistics.
Exploring the use of large-scale language data in linguistic research, this module introduces corpus linguistics as a powerful methodology for investigating patterns of language use. Students will examine the principles of corpus design, construction, annotation, and analysis, considering the theoretical, practical, and ethical decisions involved in creating and using language corpora. The module develops skills in applying statistical and computational techniques to explore linguistic phenomena such as meaning, variation, discourse, and style, using a range of corpus tools and analytical methods. Through the design and execution of an independent corpus-based investigation, students will develop the ability to conduct rigorous, evidence-based research and critically evaluate language patterns in authentic datasets.
Examining the latest developments in artificial intelligence, this module explores how modern AI systems are designed, trained, and applied to address complex real-world challenges. Students will investigate contemporary approaches including machine learning, deep learning, generative AI, and intelligent agents, evaluating their capabilities, limitations, and practical applications across a range of domains. The module combines technical understanding with critical reflection, encouraging students to assess the ethical, societal, and organisational implications of AI technologies while developing evidence-based solutions to real-world problems.
Developing the foundations of modern data-driven intelligence, this module introduces students to the core concepts, algorithms, and workflows that underpin machine learning systems. Students will explore supervised and unsupervised learning techniques, learning how different algorithms can be applied to tasks such as classification, regression, clustering, and dimensionality reduction. The module examines approaches to model evaluation, validation, and performance assessment, enabling students to critically interpret results and identify the strengths and limitations of different methods. Alongside technical development, students will consider issues of fairness, bias, interpretability, and responsible AI, developing a critical understanding of the opportunities and challenges associated with deploying machine learning systems in real-world contexts.
Exploring the computational analysis of human language, this module develops students’ understanding of the methods, techniques, and tools used to process, analyse, and extract meaning from text. Students will investigate the core stages of the natural language processing pipeline, including tokenisation, text normalisation, parsing, named entity recognition, classification, and information extraction. The module examines both rule-based and statistical approaches to language processing, enabling students to evaluate their suitability for different linguistic tasks and applications. Through practical engagement with widely used NLP tools and libraries, students will develop the skills required to analyse language data and implement solutions to real-world language problems. The module also encourages critical reflection on the ethical and societal implications of NLP technologies, including issues of bias, privacy, intellectual property, and responsible innovation.
Exploring the scientific principles that underpin human interaction with technology, this module examines how cognitive, perceptual, and physical processes shape the design and use of interactive systems. Students will investigate key concepts from cognitive science, human-computer interaction, and interaction design, evaluating the frameworks and models used to understand and predict user behaviour. Through the application of user-centred design principles, students will develop and assess interactive prototypes, drawing on empirical methods to evaluate usability and user experience. The module equips students with the knowledge and practical skills required to design, test, and communicate effective technology solutions informed by an understanding of human behaviour.
Exploring one of the most significant developments in contemporary artificial intelligence and computational linguistics, this module examines the architectures, methods, and applications that underpin large language models (LLMs). Students will investigate transformer architectures, self-attention mechanisms, pre-training strategies, and the processes involved in training, fine-tuning, and deploying language models at scale. Through practical engagement with pre-trained LLMs, students will apply these technologies to a range of natural language processing tasks, critically evaluating their performance, capabilities, and limitations. The module also considers the wider ethical, social, and environmental implications of large-scale language modelling, encouraging students to reflect on issues of fairness, bias, interpretability, sustainability, and responsible AI deployment.

Move into AI, NLP, and language technology roles

The online Computational Linguistics Diploma helps you develop the skills needed to pursue opportunities across the rapidly growing fields of AI, language technology, and data science. With this Postgraduate Diploma, you can become a professional skilled in working with language data, machine learning, and AI-powered systems.

Explore potential career paths

Senior NLP Engineer £92,869 per year1

Senior AI Analyst £68,427 per year2

Value of a diploma (PGDip)

A Postgraduate Diploma (PGDip) is a flexible alternative to a master’s if you want to advance your career without committing to a longer programme. You’ll gain advanced, industry-relevant knowledge in a streamlined format, allowing you to focus on the skills that matter most. You’ll be able to:

  • Study relevant modules only.
  • Graduate sooner with a Level 7 qualification.
  • Reduce your overall tuition costs.
  • Apply practical skills immediately.
  • Progress to your MSc when you’re ready.

Programme outcomes

By the end of the Postgraduate Diploma in Computational Linguistics, you’ll be able to:

  • Understand how language works and how AI systems process information to interpret and generate human communication
  • Apply natural language processing (NLP), machine learning, and AI techniques to address real-world language challenges
  • Use both qualitative and quantitative approaches to analyse and interpret complex language data
  • Design, build, and assess language technology solutions for practical applications
  • Make informed, ethical decisions when developing and deploying AI-powered language technologies

Entry criteria

Application Deadline 02/11/27

Start Date 03/01/27

The online Postgraduate Diploma is designed for graduates from a broad range of related disciplines who share a passion for humanities and sciences. While we seek applicants with a bachelor’s degree, we do consider those with relevant work experience.

Online applicationApply Now
DegreeTypically, applicants hold a 2:2 bachelor’s degree (or equivalent). Applicants with substantial professional experience may also be considered.
Language criteriaIf English is not your first language, you’ll usually need an IELTS overall score of 6.5 (with no band below 6.0). In some cases, this may be waived based on prior study, supporting access for a global cohort.
Admissions

Tuition and funding

£9,600 Total cost

120 Total credits

The estimated total cost of this programme is £9,600 GBP for the full PGDip. You can pay in full or in instalments of £1,200 for each module. All costs are listed to help you make an informed decision.

Programme fees are reviewed annually and are subject to change each academic year. The fees listed above are for the academic year 2026-27.

Fees and funding

We are excited to be offering discounts. Review our tuition and funding pages for more information.

Funding options

Meet your faculty

Our expert faculty offer extensive knowledge and diverse perspectives, bringing industry insights and real-world expertise directly into the classroom to enhance your learning experience.

  • Academics with advanced qualifications and specialised expertise
  • Real-world experience integrated into coursework and discussion
  • A learning environment that blends academic rigour with structured support
  • Smaller study groups that enable individual attention and feedback
  • Ongoing mentorship and support at each stage of your studies at Goldsmiths
Dr Tony Russell-Rose

Dr Tony Russell-Rose, Reader in Computer Science, Computational Linguistics

Dr Tony Russell-Rose

Dr Tony Russell‑Rose is a Reader in Computer Science in the Department of Computing at Goldsmiths, University of London, whose work explores how people search for and interact with information online. His research focuses on the intersection of natural language processing, information retrieval, and user experience, with particular interests in human-information interaction, exploratory search, and knowledge discovery. His approach combines theory with experimentation, in analysing existing practices, building novel interactive technologies and systems, and studying their impact on real users in naturalistic settings.

Dr Geri Popova

Dr Geri Popova, Senior Lecturer, Computational Linguistics

Dr Geri Popova

Dr. Geri Popova is a Senior Lecturer in Linguistics in the Department of Computing at Goldsmiths, University of London, with interests in core areas of linguistics, including morphosyntax, lexical semantics, formal models of linguistic structure, and the empirical investigation of linguistic phenomena in corpora. Her research has examined grammaticalization and grammatical categories across languages from both synchronic and diachronic perspectives, drawing on cross-linguistic comparisons. She has also worked in applied areas of linguistics, including discourse analysis. Her teaching spans both theoretical and applied linguistics, covering topics including core linguistics, corpus linguistics, discourse analysis, translation, and multilingualism.

Related programmes

Computational Linguistics MSc

Develop practical skills in language data analysis, machine learning, and NLP that are applicable across AI, data science, and technology careers. 

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Computational Linguistics PGCert

Gain a focused foundation in NLP, AI, and linguistics to understand and apply core language technology concepts.

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Sources

  1. Salaryexpert.com. (2026). Salary & Compensation Calculator | Compensation Hub – SalaryExpert. [online] Available at: https://www.salaryexpert.com/salary/job/nlp-engineer/united-kingdom [Accessed 9 July 2026].‌
  2. Salaryexpert.com. (2026). Salary & Compensation Calculator | Compensation Hub – SalaryExpert. [online] Available at: https://www.salaryexpert.com/salary/job/ai-engineer/united-kingdom [Accessed 9 July 2026].