Data Science and Artificial Intelligence
University of the West of Scotland
UCAS Code: G402 | Bachelor of Science (with Honours) - BSc (Hons)
University of the West of Scotland
UCAS Code: G402 | Bachelor of Science (with Honours) - BSc (Hons)
Entry requirements
A level
including Maths or Computing at GCSE Grade 5/C or above
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
in relevant subject
Scottish HNC
in appropriate subject
Scottish HND
in appropriate subject
Scottish Higher
including Maths/Applications of Maths or Computing
UCAS Tariff
including Maths/Applications of Maths or Computing
About this course
**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:
- Develop an understanding of Data Science and AI applications across industries.
- Explore the evolution and advancements in the field.
- Teach ethical practices, data privacy, and security.
- Enhance programming skills in Python, R, and SQL.
- Provide hands-on experience with real-world data projects.
- 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**
- Comprehensive learning experience – students develop intellectual, imaginative, and professional competencies, including problem-solving, communication, and teamwork.
- Strong foundation in data science & AI – the course covers programming, mathematics, software engineering, and AI principles, ensuring adaptability to technological advancements.
- Dedicated Personal Tutors – Year Leaders provide continuous guidance, supporting personal growth and career aspirations.
- High-demand skills development – students gain expertise in data analysis, programming (Python, R, SQL), AI-driven decision-making, and business intelligence.
- Practical & professional experience – hands-on projects, real-world applications, and exposure to ethical and industry standards prepare graduates for dynamic careers.
- 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 methods
A variety of assessment approaches are utilised throughout the course such as examination, written coursework, portfolio and presentations.
Tuition fees
Select where you currently live to see what you'll pay:
The Uni
Paisley Campus
Computing, Engineering and Physical Sciences
What students say
How do students rate their degree experience?
The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.
Others in computing
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This is usually because there were too few respondents in the data we receive to be able to provide results about the subject at this university.
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
Artificial intelligence
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Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
After graduation
The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.
Others in computing
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Artificial intelligence
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Artificial intelligence is a very specialist subject taken by less than 100 people a year at the moment, so there is little reliable information available on graduate prospects - bear that in mind when you review the stats above. Graduates taking this type of subject are more likely than other computing graduates to go into further research. However, if you want to find out more specifically about the potential graduate outcomes of a specific course, it's a good idea to go on open days and talk to tutors about what previous graduates have gone on to do.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Others in computing
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£20k
£24k
£25k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
Artificial intelligence
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£20k
£24k
£25k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
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Post-six month graduation stats:
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It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.
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Graduate field commentary:
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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
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