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PgCert|Postgraduate Taught

Artificial Intelligence

Entry year
2024/25
Entry requirements
2.1
Duration
1 year (Part-time)
Places available
TBC (Part Time)

In the last decade the advances in Artificial Intelligence have made it at the forefront of technology, with many advances improving our daily lives.

Such is its importance that AI has become a national priority in many countries, including the UK, US, China, and India.

As a result, there is a huge demand for specialist graduates with advanced AI knowledge and skills.

The PG Cert in Artificial Intelligence (AI) is aimed as a starting point to prepare students to embark on an industrial career or further research studies, with knowledge and skills in AI mathematics, knowledge representation and reasoning, machine learning, computer vision, natural language processing, and data analytics. They will also gain experience in applying AI knowledge and skills to develop AI systems and applications. The PG Cert will introduce core taught material, enabling students to gain a good understanding of the range of topics, and acquired skills associated with the creation, evaluation and deployment of AI systems and applications.

ABOUT YOU –
An analytical, curious, technical, and ambitious individual. You are ready to expand the horizons of what is possible.

You will appreciate the growing demand for AI in the world and would seek to use these skills to further your career in this exciting and expanding area.

Ideally, you will be a Computing graduate with strong programming skills and a solid background in mathematics.

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Artificial Intelligence highlights

Industry Links

Developed in direct response to industry need this course will provide the building blocks required for you to step into a career in AI.

World Class Facilities

Most of the lectures and lab based activities are in our Computer Science Building opened in 2016 after a £14 million re-development. The four-storey, 3,000m2, state-of-the-art facility has large well-equipped computing labs, including a dedicated AI Lab, and formal and informal student spaces which support a high level of group and project work.

Internationally Renowned Experts

The teaching team are specialists in each subject area and bring a wealth of up-to-date knowledge to the course. They have extensive research experience in their subject area and are noted for their research output.

Student Experience

The programme development team have experience in AI programme design at MSc level. This programme is newly designed to minimise module overlap, maximise employment relevancy and content recency; to consider knowledge/skill longevity and between-year continuity; to be free of legacy issues (existing course provision, staff). Four new AI staff members are recruited to best match the new design.

Industry Links

EMPLOYERS WHO ARE INTERESTED IN PEOPLE LIKE YOU:

BT, BBC, PwC, Kainos, Datactics,
Microsoft, Google, Facebook, Oosto (formerly Anyvision), etc

Career Development

WHERE WOULD YOU LIKE TO BE IN FIVE YEARS TIME ?

A thought leader in AI, showcasing technological advancements through research. Working for some of the largest companies on the planet. Or even advising government policy. The future is an exciting place, full of opportunity.

Course Structure

Taught modules will be running in block mode.

Computer Vision

This module will cover deep neural networks (DNNs) and modern approaches to computer vision including DNN models for various computer vision tasks and current topics of computer vision. It will develop the ability to utilise DNN models to solve real-world computer vision challenges, the ability to obtain image/video data from recognised repositories, the ability to utilise existing libraries and packages for implementing appropriate DNN models for a given computer vision task.

Foundations of AI

This module will cover the fundamental mathematics underlying AI including probability and statistics, calculus, algebra and optimisation. It will provide you with a sound understanding of the fundamentals; develop the ability to utilise them to understand and explain various AI techniques, and the ability to identify the most suitable modelling, optimisation, factorisation, and transformation approach for a given problem.

Machine Learning

This module will cover different types of machine learning and various algorithms of each type. It will provide you with a systematic understanding of machine learning as a subject area, develop your ability to identify problems that can be solved using machine learning methods, to apply suitable machine learning algorithms and software packages to solve real-world problems, to evaluate and compare the performance of machine learning methods for a given problem, and to present and discuss the results of machine learning methods and propose appropriate improvements to methods.

People teaching you

Professor of Artificial Intelligence

School of EEECS
h.wang@qub.ac.uk

Learning and Teaching

Learning opportunities associated with this course are outlined below:

Academic Team

You will be taught by a teaching team who are specialists in each subject area and bring a wealth of up-to-date knowledge to the course. This extensive research experience combined with projects offers you the perfect environment to study AI.

English Language Support

The school is offering support on the use of English in academic writing. This will help you not only during your studies at Queen’s, but also in your future career.

Modules

The Course is composed of three distinct modules, each intended to progressively enhance your knowledge, comprehension, and proficiencies in AI. Each module begins with a week-long pre-module onboarding reading activity, followed by an intensive block mode consisting of onsite delivery of lectures and lab activities, spanning 2-3 days each week for three weeks. Project-based assessment is conducted following the taught period. To supplement the onsite sessions, there are substantial digital resources, such as pre-lecture videos and video-ed labs, with online support sessions available beyond the onsite teaching periods.

Transferrable Skills

The objective of this course is to produce highly trained and desirable graduates who are well-prepared for the rapidly-evolving field of AI technology. Upon successfully finishing the PG Cert program, students will be qualified to pursue a full MSc in AI.

Virtual Learning Environment

All modules have a virtual learning environment (using Canvas) where the students can find all relevant material (lecture notes, handouts, video lectures) as well as online quizzes and assignments.

Assessment

Assessments associated with the course are outlined below:

  • Awarding of the qualifications is based on continuous assessment of coursework and assessment of modules is based solely on submitted work related to private, individual study.

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Modules

Modules

The information below is intended as an example only, featuring module details for the current year of study (2024/25). Modules are reviewed on an annual basis and may be subject to future changes – revised details will be published through Programme Specifications ahead of each academic year.

  • Year 1

    Core Modules

    Computer Vision (20 credits)
    Machine Learning (20 credits)
    Foundations of AI (20 credits)

Entrance requirements

Graduate

Normally a 2.1 Honours degree or equivalent qualification acceptable to the University in Computer Science, Software Engineering, Electrical and/or Electronic Engineering, Mathematics with Computer Science, Physics with Computer Science or a related discipline. Applicants must normally have achieved 2:1 standard or above in relevant modules.

Applicants who hold a 2.2 Honours degree and a Master’s degree (or equivalent qualifications acceptable to the University) in one of the above disciplines will be considered on a case-by-case basis.

All applicants will be expected to have mathematical ability and significant programming experience as evidenced either through the content of their primary degree or through another appropriate formal qualification.

Applications may be considered from those who do not meet the above requirements but can provide evidence of recent relevant technical experience in industry, for example, in programming.

The University's Recognition of Prior Learning Policy provides guidance on the assessment of experiential learning (RPEL). Please visit http://go.qub.ac.uk/RPLpolicy for more information.

AICC funding: A limited number of fully funded places (provided by the Department for the Economy) are available for this programme for eligible applicants resident in Northern Ireland. Where there are more eligible applicants than places available the academic selectors will make offers in rank order based on academic merit and potential as evidenced in the totality of the information provided within each application. We will operate a waiting list as required to allow us to fill all available places. You will be notified as soon as possible after the deadline whether your application has been selected for a funded place. If you have not been selected for a funded place, we will accept self-funded or employer-funded applicants, if spaces are available. More details can be found at the link below.

Application deadline for AICC funding is Friday 14th June at 12 noon.
https://www.qub.ac.uk/about/Leadership-and-structure/Faculties-and-Schools/Engineering-and-Physical-Sciences/AICC/

International Students

Our country/region pages include information on entry requirements, tuition fees, scholarships, student profiles, upcoming events and contacts for your country/region. Use the dropdown list below for specific information for your country/region.

English Language Requirements

Evidence of an IELTS* score of 6.5, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required. *taken within the last 2 years

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.

  • Academic English: an intensive English language and study skills course for successful university study at degree level
  • Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.

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Career Prospects

Introduction

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Prizes and Awards

Teachers working on classroom-based dissertation projects may apply for the Northern Ireland Centre for Educational Research (NICER) award .

Graduate Plus/Future Ready Award for extra-curricular skills

In addition to your degree programme, at Queen's you can have the opportunity to gain wider life, academic and employability skills. For example, placements, voluntary work, clubs, societies, sports and lots more. So not only do you graduate with a degree recognised from a world leading university, you'll have practical national and international experience plus a wider exposure to life overall. We call this Graduate Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.

Tuition Fees

Northern Ireland (NI) 1 Free for DfE Funded students (see below)
Republic of Ireland (ROI) 2 N/A
England, Scotland or Wales (GB) 1 N/A
EU Other 3 N/A
International N/A

1EU citizens in the EU Settlement Scheme, with settled status, will be charged the NI or GB tuition fee based on where they are ordinarily resident. Students who are ROI nationals resident in GB will be charged the GB fee.

2 EU students who are ROI nationals resident in ROI are eligible for NI tuition fees.

3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.

All tuition fees quoted relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.

More information on postgraduate tuition fees.

Additional course costs

Students may incur additional costs for small items of clothing and/or equipment necessary for lab or field work.

All Students

Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.

Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £75 per year for photocopying, memory sticks and printing charges.

Students undertaking a period of work placement or study abroad, as either a compulsory or optional part of their programme, should be aware that they will have to fund additional travel and living costs.

If a programme includes a major project or dissertation, there may be costs associated with transport, accommodation and/or materials. The amount will depend on the project chosen. There may also be additional costs for printing and binding.

Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen.

There are also additional charges for graduation ceremonies, examination resits and library fines.

How do I fund my study?

The Department for the Economy will provide a tuition fee loan of up to £6,500 per NI / EU student for postgraduate study. Tuition fee loan information.

A postgraduate loans system in the UK offers government-backed student loans of up to £11,836 for taught and research Masters courses in all subject areas (excluding Initial Teacher Education/PGCE, where undergraduate student finance is available). Criteria, eligibility, repayment and application information are available on the UK government website.

More information on funding options and financial assistance - please check this link regularly, even after you have submitted an application, as new scholarships may become available to you.

International Scholarships

Information on scholarships for international students, is available at www.qub.ac.uk/Study/international-students/international-scholarships.

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How to Apply

Apply using our online Queen's Portal and follow the step-by-step instructions on how to apply.

Apply now

Terms and Conditions

The terms and conditions that apply when you accept an offer of a place at the University on a taught programme of study.
Queen's University Belfast Terms and Conditions.

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