Data Science with Year of Professional Experience

Program Overview

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Data Science with Year of Professional Experience

Overview

The aim of the programme is to offer a deep and up-to-date education in data science, machine learning and artificial intelligence that prepares graduates with key knowledge, skills and competencies necessary for employment in data engineering, data analysis, data architect (as well as managerial positions on those topics), or as preparation for further research and innovation careers.

Course Structure

Introduction

Mathematics is the universal language of science while computer science is the study of the hardware and algorithms that are used in modern computer systems. Since many of the early pioneers of computer science, for instance Alan Turing, were mathematicians it is not surprising that these two subjects are closely related. This is a three-year joint degree programme between the School of Electrical and Electronic Engineering and Computer Science and the School of Maths and Physics, that combines the study of the two subjects so a holistic approach to Data Science and Machine Learning, from theory to practice, can be provided.

Stage 1

Themes may include:

• Object Oriented programming
• Databases
• Procedural Programming
• Computer Science Challenges
• Web Technologies
• Software Design Principles
• Introduction to Algebra and Analysis
• Introduction to Probability and Statistics

Stage 2

Themes may include:

• Professional Practice
• Transferable Skills for the IT Sector
• Introduction to Artificial Intelligence and Machine Learning
• Statistical Inference
• Linear Algebra
• Introduction to Enterprise Computing
• Data Structures, Algorithms and Programming Languages

Stage 3

Year of Professional Experience on Data Analysis

Stage 4

Themes may include:

• Deep learning
• Video Analytics and Machine Learning
• Concurrent Programming
• Cloud Computing
• Malware Analysis
• Fairness, Interpretability and privacy in machine learning
• Data Science Project
• Discrete Mathematics
• Stochastic Processes and Risk
• Bayesian Statistics
• Financial Mathematics
• Mathematical Methods of Quantum Information processing
• Linear models
• Information Theory

In addition to some of the above modules, students are expected to complete:

• Final year project on data Analysis

Learning and Teaching

The School has a world class reputation for research and provides excellent facilities, including access to major new research centres in Secure Information Technologies, Electronics, Communications and Information Technology and Sonic Arts. A number of modules on the course are closely linked to the research expertise of these centres and evolve and change rapidly to reflect some of the current, emerging and exciting developments in the field.

At Queen’s, we aim to deliver a high quality learning environment that embeds intellectual curiosity, innovation and best practice in learning, teaching and student support to enable student to achieve their full academic potential.

Interactive Lectures

Technologies such as Turningpoint allow interactive and active lectures, where lecturers can pool students anonymously and in real time from the slides.

Online Material and Online Lectures

Through the use of MS teams, MS Stream and Mediasite live lectures are recorded to be made available in real time or near real time. This video lectures are uploaded to Canvas learning environment, where all material, lecture content, assignment and online test are also available.

This has proved fundamental to mitigate COVID and we expect to continue in normal circumstances to allow more effective online-enhanced learning.

Assessment

Details of assessments associated with this courses are outlined below:

• The way in which you are assessed will vary according to the Learning objectives of each module. Some modules are assessed solely through project work or written assignments. Others are assessed through a combination of coursework and end of semester examinations. Details of how each module is assessed are shown in the Student Handbook which is provided to all students during their first year induction.

Feedback

As students progress through their course at Queen’s they will receive general and specific feedback about their work from a variety of sources including lecturers, module co-ordinators, placement supervisors, personal tutors, advisers of study and peers. University students are expected to engage with reflective practice and to use this approach to improve the quality of their work. Feedback may be provided in a variety of forms including:

• Feedback provided via formal written comments and marks relating to work that you, as an individual or as part of a group, have submitted.

Facilities

Students have access to a wide range of computers in world class laboratories (equipped with several hundred PCs, including powerful Alienware computers) and specialised software packages.

High performance computing facilities including a computing cluster with the following characteristics:

• 60 x 128 core Dell PowerEdge R6525 compute nodes with AMD EPYC 7702 dual 64-Core Processors (786GB RAM).
• 4 High memory nodes (2TB RAM).
• 32 x NVIDIA Tesla v100 GPUs.
• 2PB of lustre parallel file system for scratch storage.
• All compute nodes and storage are connected by EDR Infiniband fabric.
• Compute nodes run CENTOS7 operating system.

High Speed Networks link the School and university computers to powerful machines in Great Britain.

Entrance Requirements

A-level

A-level: A (Mathematics) AB including at least one from Computing/Software Systems Development (not both), Physics, Biology, Chemistry, Digital Technology, Technology and Design, Electronics, Further Mathematics or Double Award Life & Health Sciences or A-level: A* (Mathematics) BB including at least one from Computing/Software Systems Development (not both), Physics, Biology, Chemistry, Digital Technology, Technology and Design, Electronics, Further Mathematics or Double Award Life & Health Sciences

A maximum of one BTEC/OCR Single Award will be accepted as part of an applicant's portfolio of qualifications with a Distinction* being equated to a grade A at A-level and a Distinction being equated to a grade B at A-level.

Irish Leaving Certificate

H2H3H3H3H3H3 including Higher Level grade H2 in Mathematics and H3 in at least one from Computing, Physics, Biology or Chemistry

International Baccalaureate Diploma

34 points overall including 6 (Mathematics) at Higher Level plus 6,5 including at least one from Computer Science, Physics, Biology or Chemistry at Higher Level. If not offered at Higher Level/GCSE then Standard Level grade 4 in English would be accepted.

Note

All applicants must have GCSE English Language grade C/4 or an equivalent qualification acceptable to the University.

How we choose our students

Applications are dealt with centrally by the Admissions and Access Service rather than by the School of Electronics, Electrical Engineering and Computer Science. Once your application has been processed by UCAS and forwarded to Queen's, an acknowledgement is normally sent within two weeks of its receipt at the University.

Selection is on the basis of the information provided on your UCAS form, which is considered by a member of administrative staff from the Admissions and Access Service and, if appropriate, the Selector from the School. Decisions are made on an ongoing basis and will be notified to you via UCAS. These decisions can only be made on the basis of the information given and applicants must show due care and diligence when completing their applications. In particular, full details must be included about qualifications completed or still to be completed.

For entry last year, applicants must have had, or been able to achieve, a minimum of five GCSE passes at grade C/4 or better (to include English Language and Mathematics), though this profile may change from year to year depending on the demand for places. The Selector also checks that any specific entry requirements in terms of GCSE and/or A-level subjects can be fulfilled.

Offers are normally made on the basis of three A-levels. Two subjects at A-level plus two at AS would also be considered.

The offer for repeat candidates is normally the same as the offer for first time applicants. For repeat applicants acceptable grades may be held from the previous year.

A-level General Studies and A-level Critical Thinking are not normally considered as part of a three A-level offer and, although they may be excluded where an applicant is taking 4 A-level subjects, the grade achieved could be taken into account if necessary in August/September.

Applicants offering other qualifications, such as BTEC National and Higher National Certificates/Diplomas, the International Baccalaureate, Irish Leaving Certificate or an Access course, will also be considered. The same GCSE profile is usually expected of those candidates offering other qualifications.

For applicants offering Irish Leaving Certificate, please note that performance at Junior Certificate is taken into account. For last year’s entry applicants for this degree must have had, a minimum of 5 IJC grades C/Merit, though this profile may change from year to year depending on the demand for places. The Selector also checks that any specific entry requirements in terms of Leaving Certificate subjects can be satisfied.

The information provided in the personal statement and the academic reference together with predicted grades are noted but these are not the final deciding factors in whether or not a conditional offer can be made. However, they may be reconsidered in a tie break situation in August.

Applicants are not normally asked to attend for interview.

If you are made an offer then you may be invited to an Open Day, which is usually held during the second semester. This will allow you the opportunity to visit the University and to find out more about the degree programme of your choice; the facilities on offer. It also gives you a flavour of the academic and social life at Queen's.

If you cannot find the information you need here, please contact the University Admissions and Access Service (), giving full details of your qualifications and educational background.

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.

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

Tuition Fees

Northern Ireland (NI) 1 | £4,855
---|---
Republic of Ireland (ROI) 2 | £4,855
England, Scotland or Wales (GB) 1 | £9,535
EU Other 3 | £26,600
International | £26,600

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 will be subject to an annual inflationary increase in each year of the course. Fees quoted relate to a single year of study unless explicitly stated otherwise.

Tuition fee rates are calculated based on a student’s tuition fee status and generally increase annually by inflation. How tuition fees are determined is set out in the Student Finance Framework.

Additional course costs

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.

Scholarships

Each year, we offer a range of scholarships and prizes for new students. Information on scholarships available.

International Scholarships

Information on scholarships for international students, is available at

How to Apply

Application for admission to full-time undergraduate and sandwich courses at the University should normally be made through the Universities and Colleges Admissions Service (UCAS). Full information can be obtained from the UCAS website at:

When to Apply

UCAS will start processing applications for entry in autumn 2026 from early September 2025.

The advisory closing date for the receipt of applications for entry in 2026 is Wednesday 14 January 2026 (18:00). This is the 'equal consideration' deadline for this course.

Applications from UK and EU (Republic of Ireland) students after this date are, in practice, considered by Queen’s for entry to this course throughout the remainder of the application cycle (30 June 2026) subject to the availability of places. If you apply for 2026 entry after this deadline, you will automatically be entered into Clearing.

Applications from International and EU (Other) students are normally considered by Queen's for entry to this course until 30 June 2026. If you apply for 2026 entry after this deadline, you will automatically be entered into Clearing.

Applicants are encouraged to apply as early as is consistent with having made a careful and considered choice of institutions and courses.

The Institution code name for Queen's is QBELF and the institution code is Q75.

Further information on applying to study at Queen's is available at:

Apply via UCAS

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.

Additional Information for International (non-EU) Students

1. Applying through UCAS
   Most students make their applications through UCAS (Universities and Colleges Admissions Service) for full-time undergraduate degree programmes at Queen's.
2. Applying direct
   The Direct Entry Application form is to be used by international applicants who wish to apply directly, and only, to Queen's or who have been asked to provide information in advance of submitting a formal UCAS application. Find out more.
3. Applying through agents and partners
   The University’s in-country representatives can assist you to submit a UCAS application or a direct application. Please consult the Agent List to find an agent in your country who will help you with your application to Queen’s University.

Download Undergraduate Prospectus

Career Prospects

Professional Opportunities

Student completing this degree are expected to move to a professional or a research position in data analytics and machine learning, with application to different sectors: Fintech, Health and Biomedical, Security, Agriculture, etc.

Degree 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 Degree Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.

Modules

Core Modules

• Data Driven Systems (20 credits)
• Introduction to Algebra and Analysis (30 credits)
• Procedural Programming (20 credits)
• Object Oriented Programming (20 credits)
• Introduction to Probability & Statistics (30 credits)

Core Modules

• Linear Algebra (20 credits)
• Professional and Transferrable Skills (20 credits)
• Introduction to Artificial Intelligence and Machine Learning (20 credits)
• Theory of Computation (20 credits)
• Data Structures and Algorithms (20 credits)
• Statistical Inference (20 credits)

Core Modules

• Year of Professional Experience (120 credits)

Core Modules

Optional Modules

• Deep Learning (20 credits)
• Cloud Computing (20 credits)
• Malware Analysis (20 credits)
• Concurrent Programming (20 credits)

Program Outline

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Degree Overview:

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Data Science with Year of Professional Experience (BSc)

This program aims to provide students with a comprehensive and up-to-date education in data science, machine learning, and artificial intelligence. This rigorous program prepares graduates with the knowledge, skills, and competencies necessary for various exciting career paths:

• Data engineering
• Data analysis
• Data architect
• Managerial positions in data-related fields
• Further research and innovation careers

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Specific program objectives include:

• In-depth understanding:
Providing students with a comprehensive understanding of the fundamental principles of artificial intelligence, data science, and machine learning, regardless of future technology changes.
• Advanced knowledge and skills:
Equipping students with the advanced knowledge and practical skills required for the theory and practice of data analytics, including the necessary tools and techniques for pursuing careers in this field.
• Real-world skills:
Enabling students to acquire a range of practices, processes, tools, and methods applicable to data science in commercial and research contexts.
• Exposure to current trends:
Offering students timely exposure to and practical experience in a range of current technologies and emerging trends, such as Deep Learning, Natural Language Processing, and Trustworthy AI.
• Development of practical skills:
Providing opportunities for students to develop practical skills in a commercial context through a dedicated year of professional experience with leading data analytics companies.

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Outline:

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Program Structure:

• Three-year joint degree program
between the School of Electrical and Electronic Engineering and Computer Science and the School of Maths and Physics.
• Combines the study
of mathematics, computer science, data science, machine learning, and artificial intelligence for a holistic approach to the field.

---

Stage 1 Themes:

• Object Oriented programming
• Databases
• Procedural Programming
• Computer Science Challenges
• Web Technologies
• Software Design Principles
• Introduction to Algebra and Analysis
• Introduction to Probability and Statistics

---

Stage 2 Themes:

• Professional Practice
• Transferable Skills for the IT Sector
• Introduction to Artificial Intelligence and Machine Learning
• Statistical Inference
• Linear Algebra
• Introduction to Enterprise Computing
• Data Structures, Algorithms and Programming Languages

---

Stage 3:

• Year of Professional Experience on Data Analysis

---

Stage 4 Themes:

• Deep learning
• Video Analytics and Machine Learning
• Concurrent Programming
• Cloud Computing
• Malware Analysis
• Fairness, Interpretability and privacy in machine learning
• Data Science Project
• Discrete Mathematics
• Stochastic Processes and Risk
• Bayesian Statistics
• Financial Mathematics
• Mathematical Methods of Quantum Information processing
• Linear models
• Information Theory

---

Additional Modules:

• Final year project on data Analysis
• Learning and Teaching

---

Teaching:

• The School has a world-class reputation for research and provides excellent facilities, including access to major new research centres in Secure Information Technologies, Electronics, Communications and Information Technology and Sonic Arts.
• Many modules on the course are closely linked to the research expertise of these centres and evolve and change rapidly to reflect some of the current, emerging and exciting developments in the field.

---

Interactive Learning:

• Technologies such as Turningpoint allow interactive and active lectures, where lecturers can poll students anonymously and in real time from the slides.
• Online Material and Online Lectures: Through the use of MS Teams, MS Stream and Mediasite live lectures are recorded to be made available in real time or near real time.
This video lectures are uploaded to Canvas learning environment, where all material, lecture content, assignment and online test are also available.

---

Assessment:

• Methods of assessment will vary according to the Learning objectives of each module.
• Some modules are assessed solely through project work or written assignments, while others are assessed through a combination of coursework and end of semester examinations.
• Further details about the assessment for each module are provided in the Student Handbook.

---

Feedback:

• Students will receive general and specific feedback about their work from a variety of sources, including lecturers, module coordinators, placement supervisors, personal tutors, advisers of study and peers.
• Students are expected to engage with reflective practice and to use this approach to improve the quality of their work.
• Feedback may be provided in various forms, such as:
• Written comments and marks related to work submitted individually or as part of a group.
• Feedback provided via formal written comments and marks relating to work that you, as an individual or as part of a group, have submitted.

---

Facilities:

• Students have access to a wide range of computers in world-class laboratories (equipped with several hundred PCs, including powerful Alienware computers) and specialized software packages.
• High-performance computing facilities including a computing cluster with the following characteristics:
• 60 x 128 core Dell PowerEdge R6525 compute nodes with AMD EPYC 7702 dual 64-Core Processors (786GB RAM).
• 4 High memory nodes (2TB RAM).
• 32 x NVIDIA Tesla v100 GPUs.
• 2PB of lustre parallel file system for scratch storage.
• All compute nodes and storage are connected by EDR Infiniband fabric.
• Compute nodes run CENTOS7 operating system.
• High-Speed Networks link the School and university computers to powerful machines in Great Britain.

---

Other:

• The program offers students a unique opportunity to gain valuable professional experience through a dedicated year working with leading data analytics companies.
This experience allows students to apply their theoretical knowledge to real-world challenges, develop their practical skills, and build their professional network.
• The program provides students with access to world-class facilities and resources, including high-performance computing clusters, specialized software packages, and a dedicated team of academic and industry experts.
• This ensures that students have the necessary tools and support to succeed in their studies and future careers.

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Tuition Fees and Payment Information:

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Northern Ireland (NI) 1:

£4,750

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Republic of Ireland (ROI) 2:

£4,750

---

England, Scotland or Wales (GB) 1:

£9,250

---

EU Other 3:

£25,300

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International:

£25,300

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Additional course costs:

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All Students

• Books and learning resources: £30 - £100 per year
• Photocopying, memory sticks and printing charges: £30 - £75 per year
• Work placement or study abroad costs: Variable depending on location and duration
• Major project or dissertation costs: Variable depending on project chosen

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International and EU (Other) students:

Applications are normally considered until 30 June 2025. In addition, all tuition fees will be subject to an annual inflationary increase in each year of the course.