Natural Language Processing (MSc)
- Duration: 1 year
- Mode: Full time
Open day
Find out more about studying here as a postgraduate at our next Open Day.
Why study this course
This programme aims to develop your technical capabilities as well as a critical understanding of the ethical and social impacts of dealing with text data, covering technical aspects of the most recent and cutting-edge Natural Language Processing (NLP) technologies.
Innovative environment
We have designed our course with the most up-to-date research, co-designed by world-renowned NLP researchers.
Build your skillset
Acquire transferable NLP skills from a multi-disciplinary teaching team that are sought after in a broad range of sectors.
Industry ready
You will benefit from visiting lecturers from relevant industries, gaining exposure to state-of-the-art production-ready NLP technologies.
Text data is a fundamental source of information in the 21st century. Natural Language Processing (NLP), the branch of AI that deals with this type of data, is in massively high demand both in academia and industry.
This programme aims to develop your technical capabilities as well as a critical understanding of the ethical and social impacts of dealing with text data, covering technical aspects of the most recent and cutting-edge Natural Language Processing (NLP) technologies. Moreover, the course will emphasize both the engineering and the research aspects of the field, thereby equipping you with a unique skillset valuable for both industry and academic career pathways.
Graduates from the programme will be ideally placed for employment in the NLP industry - including areas such as finance, defence, retail, manufacturing or social media. High-performing graduates from this programme will be well-prepared for commencing a research career in Artificial Intelligence.
Where you'll study
School of Computer Science and Informatics
Our degree programmes are shaped by multidisciplinary research, making them relevant to today's employers and well placed to take advantage of tomorrow's developments.
Admissions criteria
In order to be considered for an offer for this programme you will need to meet all of the entry requirements. Your application will not be progressed if the information and evidence listed is not provided.
With your online application you will need to provide:
- A copy of your degree certificate and transcripts which show you have achieved a 2:1 honours degree in a relevant area such as computer science, computing, linguistics, or mathematics, or an equivalent international degree. If your degree certificate or result is pending, please upload any interim transcripts or provisional certificates.
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A copy of your IELTS certificate with an overall score of 6.5 with 6.0 in all subskills, or evidence of an accepted equivalent. Please include the date of your expected test if this qualification is pending. If you have alternative acceptable evidence, such as an undergraduate degree studied in the UK, please supply this in place of an IELTS.
If you do not have a degree in a relevant area or have a 2:2 honours degree you may still apply but should provide additional evidence to support your application such as a CV and references. You may be required to take part in an interview.
Application Deadline
We allocate places on a first-come, first-served basis, so we recommend you apply as early as possible. Applications normally close at the end of August but may close sooner if all places are filled.
Selection process
We will review your application and if you meet all of the entry requirements, we will make you an offer.
Find out more about English language requirements.
Applicants who require a Student visa to study in the UK must present an acceptable English language qualification in order to meet UKVI (UK Visas and Immigration) requirements.
Criminal convictions
You are not required to complete a DBS (Disclosure Barring Service) check or provide a Certificate of Good Conduct to study this course.
If you are currently subject to any licence condition or monitoring restriction that could affect your ability to successfully complete your studies, you will be required to disclose your criminal record. Conditions include, but are not limited to:
- access to computers or devices that can store images
- use of internet and communication tools/devices
- curfews
- freedom of movement
- contact with people related to Cardiff University.
Course structure
This is a two-stage programme taught over one year for a total of 180 credits. The taught stage is 120 credits, followed by a 60-credit research project. All modules in the taught stage are worth 20 credits.
The dissertation stage of your degree will be an individual project (worth 60 credits) which you will write up as a dissertation, after the taught stage. This project will be carried out the summer under the supervision of a member of academic staff.
The modules shown are an example of the typical curriculum. Final modules will be published one month ahead of your programme starting.
Taught stage
You will study four 20-credit compulsory modules to a total of 80 credits and choose a further 40 credits from a list of carefully selected optional modules, studying 60 credits in each of the Autumn and Spring semesters, one optional module in each semester.
Dissertation Stage
Following successful completion of the taught stage you will go on to the dissertation stage and complete your 60-credit dissertation project undertaken in the summer.
| Module title | Module code | Credits |
|---|---|---|
| Machine Learning for NLP | CMT122 | 20 credits |
| Advanced Topics in NLP | CMT227 | 20 credits |
| Computational Data Science | CMT309 | 20 credits |
| Computational Linguistics | CMT318 | 20 credits |
| NLP Dissertation | CMT405 | 60 credits |
| Module title | Module code | Credits |
|---|---|---|
| Knowledge Representation | CMT117 | 20 credits |
| Distributed and Cloud Computing | CMT202 | 20 credits |
| Human Centric Computing | CMT206 | 20 credits |
| Automated Reasoning | CMT215 | 20 credits |
| Data Visualisation | CMT218 | 20 credits |
| Databases and Modelling | CMT220 | 20 credits |
| Principles of Machine Learning | CMT311 | 20 credits |
| Foundations of Statistics and Data Science | MAT022 | 20 credits |
The University is committed to providing a wide range of module options where possible, but please be aware that whilst every effort is made to offer choice this may be limited in certain circumstances. This is due to the fact that some modules have limited numbers of places available, which are allocated on a first-come, first-served basis, while others have minimum student numbers required before they will run, to ensure that an appropriate quality of education can be delivered; some modules require students to have already taken particular subjects, and others are core or required on the programme you are taking. Modules may also be limited due to timetable clashes, and although the University works to minimise disruption to choice, we advise you to seek advice from the relevant School on the module choices available.
Learning and assessment
How will I be taught?
The School of Computer Science and Informatics has a strong and active research culture which informs and directs our teaching. We are committed to providing teaching of the highest standard.
A diverse range of teaching and learning styles are used throughout this programme. Modules are delivered through a series of either full- or half-day contact sessions, which include lectures, seminars, workshops, tutorials and laboratory classes. These are delivered both from academic staff and industry experts, including members from the Advanced Research Computing facilities (ARCCA), who will focus on leveraging high performance computing hardware for NLP.
Most of your taught modules will have further information for you to study and you will be expected to work through this in your own time according to the guidance provided by the lecturer for that module.
Formative class and laboratory exercises will allow you to practice the skills you will learn, gain feedback on your progress, and provide you with the support you need to continue to develop further
You will also undertake a project and independent study to enable you to complete your dissertation. Dissertation topics may be suggested by yourself or chosen from a list of options proposed by academic staff and industrial partners, reflecting their current interests. Which projects are available to you will be confirmed during the project selection phase, and may depend on the modules you take, and supervisor/industrial partner availability.
What opportunities are available to study through the medium of Welsh?
Personal tutoring, assessments and seminars can be provided in Welsh.
How will I be assessed?
The taught modules within the programme are assessed through a wide range of assessments, such as: practical assignments; written reports; essays; examinations.
Feedback on coursework may be provided via written comments on work submitted, by provision of ‘model’ answers and/or through discussion in contact sessions.
The individual project and dissertation enable you to demonstrate your ability to build upon and exploit knowledge and skills gained in earlier stages of the Programme. Furthermore, it provides the opportunity for you to exhibit critical and original thinking based on a period of independent study and learning
How will I be supported?
We pride ourselves on providing a supportive environment in which we are able to help and encourage our students.
At the start of your course you will be allocated a Personal Tutor who is an academic member of staff in the School and serves as a point of contact to advise on both academic and personal matters in an informal and confidential manner. Your Personal Tutor will monitor your progress throughout your time at university and will support you in your Personal Development Planning.
Outside of scheduled tutor sessions, our Senior Personal Tutor runs an open-door policy, being on hand to advise and respond to any personal matters as they arise.
What skills will I practise and develop?
The Learning Outcomes for this Programme describe what you will achieve by the end of your programme at Cardiff University and identify the knowledge and skills that you will develop. They will also help you to understand what is expected of you.
On successful completion of your Programme you will be able to:
The Learning Outcomes for this Programme describe what you will achieve by the end of your programme at Cardiff University and identify the knowledge and skills that you will develop. They will also help you to understand what is expected of you.
On successful completion of your Programme you will be able to:
Knowledge & Understanding:
KU 1 systematically express the importance of data curation in the success of NLP methods.
KU 2 recognise and review the key concepts and algorithms underlying NLP methods.
KU 3 evaluate the theoretical properties of different NLP methods
KU 4 critically assess how NLP methods influence the success of a given task
Intellectual Skills:
IS 1 implement and evaluate NLP methods to solve a given task
IS 2 explain and communicate the fundamental principles underlying common NLP methods
IS 3 critically appraise the ethical implications and societal risks associated with the deployment of NLP methods
Professional Practical Skills:
PS 1 formalize real-world problems in relation to chosen NLP methods
PS 2 determine the appropriate NLP method (and data curation strategy if needed) to address the needs of a given application setting
PS 3 undertake an individual NLP project, carry out critical evaluation of findings and communicate the results clearly.
Transferable/Key Skills:
KS 1 appraise and critique your own and other’s work through written and verbal means
KS 2 communicate complex ideas, principles and theories clearly by oral, written and practical means, to a range of audiences
KS 3 reflect upon and develop opportunities for career development
KS 4 undertake independent study and critical reflection
Tuition fees for 2025 entry
Your tuition fees and how you pay them will depend on your fee status. Your fee status could be home, island or overseas.
Learn how we decide your fee status
Fees for home status
| Year | Tuition fee | Deposit |
|---|---|---|
| Year one | £11,700 | None |
Students from the EU, EEA and Switzerland
If you are an EU, EEA or Swiss national, your tuition fees for 2025/26 be in line with the overseas fees for international students, unless you qualify for home fee status. UKCISA have provided information about Brexit and tuition fees.
Fees for island status
Learn more about the postgraduate fees for students from the Channel Islands or the Isle of Man.
Fees for overseas status
| Year | Tuition fee | Deposit |
|---|---|---|
| Year one | £31,700 | £2,500 |
More information about tuition fees and deposits, including for part-time and continuing students.
Financial support
Financial support may be available to individuals who meet certain criteria. For more information visit our funding section. Please note that these sources of financial support are limited and therefore not everyone who meets the criteria are guaranteed to receive the support.
Additional costs
Will I need any specific equipment to study this course/programme?
You will need to provide your own laptop. Information regarding the particular laptop specification required will be provided in advance of enrolment. You will be provided with access to all required software at no additional cost.
Various support schemes are available to ensure all our students have access to the necessary equipment, subject to eligibility.
Living costs
We’re based in one of the UK’s most affordable cities. Find out more about living costs in Cardiff.
Funding
Career prospects
Graduates from this programme will be ideally placed to develop careers as data scientists, machine learning engineers, NLP engineers and research scientists. Technical skills will be complemented with critical thinking, teamwork and environmental and ethical awareness, which will be covered in the context of developing NLP datasets and models. Moreover, by interacting with visiting lecturers from relevant industries, students will be exposed to state-of-the-art production-ready NLP technologies, and will be able to work with real-world datasets. The research-led teaching that the programme features enables graduates to develop technical independence, critical thinking and problem solving.
Next steps
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HESA Data: Copyright Higher Education Statistics Agency Limited 2021. The Higher Education Statistics Agency Limited cannot accept responsibility for any inferences or conclusions derived by third parties from its data. Data is from the latest Graduate Outcomes Survey 2019/20, published by HESA in June 2022.
