Course contact details
Applicant Enquiry Team
Email:ask@uws.ac.uk
Phone:0800 027 1000
Fax: 0141 887 0812
University of the West of Scotland
Paisley Campus
High Street
Paisley
PA1 2BE
Data Science and Artificial Intelligence
- BSc (Hons)
- 4 Years
- Full-time
- 7 September 2026
- Undergraduate
- Paisley Campus
Course summary
Overview
Data Science and Artificial Intelligence (AI) is a rapidly evolving field that integrates data analysis, machine learning, statistical modelling, and data visualisation. This programme equips students with essential skills in data manipulation, algorithm development, and ethical considerations, preparing them for careers in data-driven industries.
Course aims:
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Develop an understanding of Data Science and AI applications across industries.
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Explore the evolution and advancements in the field.
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Teach ethical practices, data privacy, and security.
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Enhance programming skills in Python, R, and SQL.
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Provide hands-on experience with real-world data projects.
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Strengthen skills in data visualisation and business intelligence.
Graduates will be well-prepared for technical roles in data analysis, machine learning, and AI-driven decision-making, contributing to business strategy and innovation. This programme also provides a strong foundation for postgraduate studies in Data Science and AI.
Course highlights
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Comprehensive learning experience – students develop intellectual, imaginative, and professional competencies, including problem-solving, communication, and teamwork.
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Strong foundation in data science & AI – the course covers programming, mathematics, software engineering, and AI principles, ensuring adaptability to technological advancements.
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Dedicated Personal Tutors – Year Leaders provide continuous guidance, supporting personal growth and career aspirations.
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High-demand skills development – students gain expertise in data analysis, programming (Python, R, SQL), AI-driven decision-making, and business intelligence.
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Practical & professional experience – hands-on projects, real-world applications, and exposure to ethical and industry standards prepare graduates for dynamic careers.
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Strong career prospects – graduates will excel in data-driven roles, contributing to business strategy, technological innovation, and research.
Careers
Graduates of BSc (Hons) Data Science and Artificial Intelligence can pursue careers in diverse industries, including technology firms, financial institutions, healthcare, retail, government agencies, and consulting firms. Common roles include Data Scientist, Machine Learning Engineer, AI Researcher, Business Intelligence Analyst, Software Engineer, and Data Engineer.
Graduates may find employment in leading global companies such as Google, Amazon, Microsoft, IBM, banks, fintech startups, and healthcare providers, with opportunities in major tech hubs like London, New York, San Francisco, Berlin, and Singapore.
For further study, graduates can pursue MSc or PhD programmes in Data Science, AI, Machine Learning, or Cybersecurity, leading to advanced research and specialised careers in academia or industry innovation.
Course Details
The BSc (Hons) Data Science and Artificial Intelligence programme provides a comprehensive foundation in computing, data science, and AI. Students begin with Introduction to Programming, Software Engineering, and Database Systems, alongside Applied Mathematics and Probability & Statistics to develop analytical skills.
As they progress, they study Data Structures & Algorithms, Network & Cloud Computing, DevOps, and Cloud Architectures, enhancing their technical expertise. Advanced topics include Big Data, Data Engineering, Artificial Intelligence Applications, and Advanced Machine Learning, equipping students with real-world AI and data science competencies.
The course also emphasises professional development, research methods, and ethical computing practices, culminating in a Computing Honours Project, where students apply their knowledge to solve industry challenges.
Modules
Year 1
Introduction to Programming
Introduction to Software Engineering
Database Systems
Applied Mathematics
Analysis of Data
ASPIRE 1
Year 2
Intermediate Programming
Introduction to Network and Cloud Computing
Software Engineering Practice
Data Structures & Algorithms
ASPIRE 2
Probability and Statistics
Year 3
Research Methods in Computing
Professional Computing Practice
DevOps
Mathematics for Data Science
Fundamentals of Data Science
Data Visualisation
Algorithms & Collections
Cloud Services and Architectures
Statistical Estimation and Inference
Year 4
Computing Honours Project
Data Engineering
Artificial Intelligence Applications
Big Data
Advanced Machine Learning
Decision Support Systems
Assessment method
A variety of assessment approaches are utilised throughout the course such as examination, written coursework, portfolio and presentations.
Qualified teacher status (QTS)
To work as a teacher at a state school in England or Wales, you will need to achieve qualified teacher status (QTS). This is offered on this course for the following level:
- Course does not award QTS
How to apply
Apply by
14 January
This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.
Application codes
- Course code:
- G402
- Institution code:
- U40
- Campus name:
- Paisley Campus
- Campus Code:
- P
Points of entry
The following entry points are available for this course:
- Year 1
- Year 2
International applicants
Students from non-EU/non-EEA countries can apply directly to UWS via our dedicated online application system. The latest we can process your application is 6 weeks before the course start date to allow for visa processing times.
Entry requirements
UCAS Tariff 90 points
including Maths/Applications of Maths or Computing
A level CCD
including Maths or Computing at GCSE Grade 5/C or above
For Year 2 entry, BBC including Computing or Maths
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016) MMM
in relevant subject
Scottish Higher BCCC
including Maths/Applications of Maths or Computing
Scottish Advanced Higher CCD
For year 2 entry, including Computing or Mathematics
Scottish HNC Pass
Year 2 entry with an HNC in the following titles: Computing (including Computer Programming); Computing Science; Software Development
Scottish HND Pass
in appropriate subject
Year 1 Entry with SWAP Access to STEM with Grades BBB
Applicants to the BSc (Hons) Data Science and Artificial Intelligence programme at UWS will benefit from possessing the following desirable skills and attributes prior to application:
Basic programming knowledge: familiarity with languages like Python, R, or Java will be advantageous.
Mathematical aptitude: a good foundation in algebra, statistics, or calculus is helpful for understanding key concepts in data science and AI.
Analytical thinking: the ability to approach problems methodically and critically evaluate data or processes.
Digital literacy: comfort with basic computer applications, cloud platforms, or data management tools.
Communication skills: proficiency in written and verbal communication for articulating ideas and collaborating effectively.
Curiosity and innovation: a keen interest in technology trends, AI advancements, and data-driven solutions.
Time management: strong organisational skills to manage coursework and independent study effectively.
While not mandatory, these skills will give prospective students a head start in mastering the challenges and opportunities presented in this rapidly evolving field.
Minimum Qualification Requirements
UCAS Tariff 63 points
including Maths or Computing
Scottish Higher CCC
including Maths/Applications of Maths or Computing
Alternative Minimum Entry Requirements: CC (42 UCAS Tariff points), including Maths or Computing, PLUS successful completion of one of the following:
UWS Foundation Academy
Foundation Apprenticeship
UWS Next Steps to University module
Top-Up
LEAPS
Applicants to the BSc (Hons) Data Science and Artificial Intelligence programme at UWS will benefit from possessing the following desirable skills and attributes prior to application:
Basic programming knowledge: familiarity with languages like Python, R, or Java will be advantageous.
Mathematical aptitude: a good foundation in algebra, statistics, or calculus is helpful for understanding key concepts in data science and AI.
Analytical thinking: the ability to approach problems methodically and critically evaluate data or processes.
Digital literacy: comfort with basic computer applications, cloud platforms, or data management tools.
Communication skills: proficiency in written and verbal communication for articulating ideas and collaborating effectively.
Curiosity and innovation: a keen interest in technology trends, AI advancements, and data-driven solutions.
Time management: strong organisational skills to manage coursework and independent study effectively.
While not mandatory, these skills will give prospective students a head start in mastering the challenges and opportunities presented in this rapidly evolving field.
English language requirements
| Test | Grade | Additional details |
|---|---|---|
| IELTS (Academic) | 6 | IELTS 6.0 with 5.5 minimum in each skill / component. |
| Cambridge English Advanced | 176 overall with no sub-test less than 169 | |
| Cambridge English Proficiency | 176 overall with no sub-test less than 169 | |
| Trinity ISE | Pass | ISEII with the minimum of a Pass in all sub-tests |
| PTE Academic | 54 | An overall score of 54 with no element below 51 |
| TOEFL (iBT) | 78 | no sub-test less than: Reading: 17; Listening: 17; Speaking: 17; Writing: 17 |
For applicants whose first language is not English, the University sets a minimum English Language proficiency level. The reason for this is that it’s essential that you are able to read, speak and understand the English language to get the most out of your time at UWS.
All international applicants are required to meet minimum English language standards, with the exception of:
// Native speakers of English
// Erasmus students (unless advised otherwise)
// non-Erasmus students from EU partner institutions (your institution must provide confirmation of your English language ability in the absence of a formal qualification)
The qualifications above must have been gained within two years prior to the start of your course at UWS.
UWS's English language requirements https://www.uws.ac.uk/international/english-language-requirements/
Contextual admissions
Universities and colleges consider more than grades when assessing applications and may make offers based on a range of criteria. Learn more about contextual offers.
UWS is Scotland’s leading widening participation university. At UWS, widening access is central to our institution. We believe in supporting and enabling students to achieve their potential regardless of their background.
Widening access addresses patterns of under-representation in higher education. It's also part of a governmental education policy in Scotland and the UK. Widening access attempts to increase the proportion of people entering higher education, from under-represented groups.
Learn more on the University of the West of Scotland website
Historical entry grades data
This section shows the range of grades that students who received offers were previously accepted on to this course with (learn more).
It is designed to support your research but does not guarantee whether you will or won't get a place.
Admissions teams consider various factors, including interviews, subject requirements, and entrance tests. Check all course entry requirements for eligibility.
Not enough data available
We are unable to show previous accepted grades for this course. This could be because the course is new, it's a postgraduate course, there isn't enough historical data, or the provider has opted out of sharing their entry grades data for this course - learn more.
Fees and funding
Tuition fees
Per year tuition fees
| Location | Fee | Year |
|---|
* This is a provisional fee and subject to change.
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website.
Additional fee information
TUITION FEE INFORMATION - SCOTTISH STUDENTS:
Eligible Scottish domiciled students can usually apply to have their tuition fees paid for them each year of their studies by the Student Awards Agency Scotland (SAAS). If you're not sure about your eligibility, you should contact SAAS. You need to apply to SAAS each year of study to have your tuition fees paid directly to UWS.
TUITION FEE INFORMATION - UK, IRISH & GIBRALTARIAN STUDENTS:
Eligible students who are domiciled in England, Wales, or Northern Ireland as well as from the Channel Islands, the Isle of Man, Gibraltar or the Republic of Ireland will qualify for tuition fees of £9,250 per academic session of study to a maximum of three years if you are studying on a four year bachelor degree course (eg. BAcc (Hons) / BA (Hons) / BEng (Hons) / BSc (Hons)). So, if your degree is four years' duration, you will only be charged tuition fees for three years. Similarly, if you are studying a five year integrated master's degree course (eg. MEng (Hons)) the you will only be charged tuition fees for four years.
TUITION FEE INFORMATION - INTERNATIONAL (NON-EU) & EU STUDENTS:
These tuition fees apply to all non-EU, EEA, and all other EU students (excluding those from Republic of Ireland and Gibraltar, whose fee level is as per UK (non-Scottish) students - see section above for more details).
ADDITIONAL COSTS:
The cost of attending university is an investment in your future career.
In addition to tuition fees and living expenses, some courses involve extra costs such as consumable study materials, field trips, equipment and uniforms. You may also want to purchase some core texts and technology such as a new laptop etc. Some of these additional costs are optional, some, such as uniforms or safety equipment may be mandatory.
Check the course entry on our website for more more information.
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