Artificial Intelligence with a Professional Placement Year (MSc)
- Duration: 2 years
- Mode: Full time with sandwich year
Open day
Find out more about studying here as a postgraduate at our next Open Day.
Why study this course
Explore the techniques and applications of artificial intelligence (AI) and develop your practical skills through exposure to real-world problems and datasets.
Explore the techniques and applications of artificial intelligence (AI) and develop your practical skills through exposure to real-world problems and datasets.
Learn the ethical and social impacts of AI technologies while developing your critical judgement, intellectual integrity and practical skills on client-facing projects.
This unique course provides specialist knowledge in areas such as automated reasoning, knowledge representation and machine learning. You also have the opportunity to customise your learning experience to suit your interests and career aspirations by choosing from a range of optional modules, professional work placements and projects.
You will apply for a paid 7-12 month professional work placement to be undertaken on completion of the taught phase of the program. This provides valuable work experience to develop your IT Professional skills. You will be supported in finding and applying for this placement, but it should be noted that this may not be in an AI specific area, and the main focus for the placement is around employability skills related to your degree.
Graduates from the programme will be ideally placed to develop careers such as data scientists, artificial intelligence engineers, and data engineers.
This two-year degree falls under the umbrella of the Data Science Academy (DSA), run by the School of Computer Science and Informatics.
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 subject area such as Computer Science or Computing, or an equivalent international degree. If your degree certificate or result is pending, please upload any interim transcripts or provisional certificates.
- 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. In these cases you may be invited to participate 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 three-stage full-time degree programme taught over two years. In the taught stage you will study core modules to a total of 120 credits.
If you are successful in obtaining a placement, this will be undertaken following the taught stage of the course. Most students start their placement in the summer of Year 1, though this may be delayed if the taught phase has not been completed at this point. If you are unable to obtain a placement, you have the option of transferring to the MSc in Artificial Intelligence degree programme (without professional placement year) and continue directly with your dissertation project.
Following successful completion of your placement you will undertake a dissertation project worth 60 credits, working with and supervised by an academic supervisor within the School.
The modules shown are an example of the typical curriculum and will be reviewed prior to the 2024/25 academic year. The final modules will be published by September 2024.
Year one
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. This will be followed by a 60-credit dissertation project undertaken in the summer.
| Module title | Module code | Credits |
|---|---|---|
| Knowledge Representation | CMT117 | 20 credits |
| Automated Reasoning | CMT215 | 20 credits |
| Principles of Machine Learning | CMT311 | 20 credits |
| Applications of Machine Learning: Natural Language Processing/Computer Vision | CMT316 | 20 credits |
| Module title | Module code | Credits |
|---|---|---|
| Penetration Testing and Malware Analysis | CMT121 | 20 credits |
| Distributed and Cloud Computing | CMT202 | 20 credits |
| Human Centric Computing | CMT206 | 20 credits |
| Computer and Network Forensics | CMT216 | 20 credits |
| Cybersecurity Operations | CMT217 | 20 credits |
| Programming Paradigms | CMT304 | 20 credits |
| Developing Secure Systems and Applications | CMT310 | 20 credits |
| Foundations of Operational Research and Analytics | MAT021 | 20 credits |
| Foundations of Statistics and Data Science | MAT022 | 20 credits |
Year two: Sandwich year
Your work placement will normally last between 7 and 12 months, taking place at the end of the taught phase of the course, before your final dissertation, allowing you to practice the new skills you have learned and apply the knowledge you have acquired, in the workplace.
You will return to university following successful completion of your work placement, normally at the start of the Summer the following year to complete your dissertation.
| Module title | Module code | Credits |
|---|---|---|
| Placement | CMT305 | 120 credits |
| Dissertation | CMT400 | 60 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 students with teaching of the highest standard.
A diverse range of teaching and learning styles are used throughout the MSc Artificial Intelligence with Professional Placement Year. Modules are delivered through a series of contact sessions, which include lectures, seminars, workshops, tutorials and laboratory classes as appropriate to your programme, using a mix of online and on-campus teaching. These may include:
- face to face teaching sessions (e.g. lectures, exercise classes, demonstrations)
- on-line resources that you work through at your own pace (e.g. videos, web resources, e-books, quizzes)
- on-line interactive sessions to work with other students and staff (e.g. discussions, live streaming of presentations, live-coding, team meetings)
- face to face small group sessions (e.g. help classes, feedback sessions)
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. Further learning and support is provided through Learning Central (Cardiff University’s Virtual Learning Environment)
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.
How will I be assessed?
The taught modules within the programme are assessed through a range of assessments, which typically consist of examinations and coursework, such as written reports, portfolios, timed assessments, extended essays, practical assignments and oral presentations.
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 placement is assessed through a Portfolio of Work including Employer Evaluations, SFIA Mapping Documents, a Draft Report and a Final Report. This will show how you have developed your skills whilst on placement.
The dissertation will enable students to demonstrate their ability to build upon and exploit knowledge and skills gained to exhibit critical and original thinking based on a period of independent study and learning.
How will I be supported?
The School prides itself on offering a comprehensive support structure to ensure positive student/staff relationships. You will be assigned a member of staff to act as your personal tutor, who will serve as a point of contact to advise on both academic and personal matters in an informal and confidential manner.
The course makes use of Cardiff University’s Virtual Learning Environment (VLE) Learning Central to provide course materials, and additional information is provided online.
All teaching will take place in Cardiff and therefore you will be able to take advantage of everything that Cardiff has to offer, both in terms of the University (Libraries, Halls of Residence, Student Union etc.) and the wider city.
You will also have access to the full range of services provided by the University’s StudentSupport Service:
http://www.cardiff.ac.uk/studentsupport/
Students are responsible for finding their own placements, but the School’s Placement Officer will inform students of suitable placement opportunities. A series of workshops, talks and networking events will be scheduled in the first year to help you find a suitable placement. During the placement you will be supported by an academic supervisor who will monitor your progress and advise you and your work-based supervisor on the assessment of the placement.
Feedback:
Students have many opportunities for feedback during the contact sessions.
The school also has a student/staff panel consisting of elected student representatives and members of teaching staff who meet to discuss academic issues. In conjunction with the work of the panel, all students are provided with an opportunity to complete feedback questionnaires at the end of the Autumn and Spring semesters. These mechanisms allow the School to regularly review courses and ensure our students receive the best provision, delivered in a consistent manner, across all of our degrees.
What skills will I practise and develop?
The Learning Outcomes for this Programme can be found below:
On successful completion of the Programme you will be able to:
Knowledge & Understanding:
- Understanding of the importance of how data is represented for the success of artificial intelligence methods
- Knowledge of the key concepts and algorithms underlying artificial intelligence methods
- Understanding of the theoretical properties of different artificial intelligence methods
- Insight and foresight of how artificial intelligence methods influence the success of a given task
Intellectual Skills:
- An ability to implement and evaluate artificial intelligence methods to solve a given task
- An ability to explain and communicate the basic principles underlying common artificial intelligence methods
- Critical appraisal of the ethical implications and societal risks associated with the deployment of artificial intelligence methods
Professional Practical Skills:
- Capacity to formalize real-world problems in relation to chosen artificial intelligence methods
- Ability to choose an appropriate artificial intelligence method (and data pre-processing strategy if needed) to address the needs of a given application setting
- Competence in implementing artificial intelligence methods, taking advantage of existing libraries where appropriate
- Demonstrate competency as an IT Professional as part of the Professional Placement Year
Transferable/Key Skills:
- Critical appraisal of your own and other’s work through written and verbal means
- Clear and efficient communication of complex ideas, principles and theories by oral, written and practical means, to a range of audiences
- Appreciation of opportunities for career development
- An ability to undertake independent study and critical reflection
Tuition fees for 2024 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 2024/25 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 | £30,200 | £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.
Costs for sandwich years
During a sandwich year (e.g. year in industry, placement year or year abroad) a lower fee will apply. Full details can be found on our fees pages.
Additional costs
The School encourages students to only accept paid placement opportunities. However, students need to consider additional costs associated with the placement such as travel, accommodation etc before accepting a placement.
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, artificial intelligence engineers, and data engineers.
Next steps
Open Day visits
Register for information about our 2023 dates.Make an enquiry
Contact us for more information about this course.International
Learn more about our truly global university.Other course options
Discover more
Related searches: Computer science
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.
