MSc Data Analytics

1 Year On Campus Masters Program

Queens University Belfast

Program Overview

The MSc in Data Analytics at Queen’s University Belfast provides strong training in statistics, programming, machine learning, and applied analytics. It suits students from quantitative or computing backgrounds who want to work as data analysts, data scientists, or analytics professionals.

Curriculum Structure (Full-time, 1 Year)

Taught Phase
Students begin with modules such as Data Analytics Fundamentals, Databases & Programming Fundamentals, and Data Mining, learning core skills in data handling, statistical analysis, database design, and exploratory analytics.
They then progress to modules like Machine Learning and Frontiers in Data Analytics, where they study predictive modelling, clustering, dimensionality reduction, visual analytics, and modern data-science workflows.

Project Phase
The year concludes with an Industry-Based Project, where students apply modelling, programming and analytical methods to a real-world business or research problem.

Focus areas: “Statistics; data mining; machine learning; database systems; visual analytics; applied analytics project”

Learning outcomes: “Analyse and manage large datasets; apply machine-learning methods; build predictive models; use visual analytics; complete an industry-standard data-analytics project.”

Professional alignment: Designed to meet industry needs for analytics and data-science professionals across business, tech, government, and research sectors.

Reputation: Queen’s University Belfast is recognised for strong analytics and quantitative training, and graduates enjoy strong employability in data-driven fields.

Experiential Learning (Research, Projects, Internships etc.)

The MSc Data Analytics at Queen's University Belfast provides practical skills in statistical analysis, data mining, and business intelligence. Students apply computational techniques to real-world datasets using industry-standard software and high-performance computing resources.

Key experiential components:

Software & Tools: Data analysis and modelling using R, Python (Pandas, scikit-learn), SQL, and business intelligence platforms like SAS, Tableau, or Power BI.
Computing Facilities: Access to Queen's High-Performance Computing (HPC) centre and dedicated computer labs within the School of Electronics, Electrical Engineering and Computer Science, equipped for statistical computing and large-scale data processing.
Group Projects: Collaborative data analytics projects, often based on real business or research challenges, where student teams work through the full analytical lifecycle to derive, visualise, and present data-driven insights.
Industry & Research Links: Teaching is informed by the university's research institutes and industry connections. The final dissertation project typically involves a substantial analysis of a complex dataset, often linked to sectors like healthcare, finance, or public policy.

Progression & Future Opportunities

Graduates of Queen's University Belfast's MSc Data Analytics program achieve strong employment outcomes in high-demand sectors like tech, healthcare, banking, and finance, with the program's industry-focused projects enhancing employability in data-driven roles. The curriculum equips students with practical skills in analytics, machine learning, and data mining, leading to rapid career progression amid global demand for data experts. Many secure positions within months, supported by Queen's top-ranked careers service.

Typical job roles include:

Data Analyst
Data Scientist
Machine Learning Engineer
Business Analyst

Queen's University Belfast offers dedicated support through its Careers Service, ranked 2nd nationally, providing bespoke training, CV workshops, and job placement assistance via Graduate Plus/Future Ready programs. Employment stats show high prospects in analytics fields, though specific salary figures for this program are not detailed; general UK data analytics roles start around £30,000-£45,000 for entry-level. Key partnerships include industry-based projects with tech, banking, and healthcare firms, boosting practical exposure. The program's accreditation aligns with long-term value in recognized analytics skills, opening doors to software, insurance, and policing sectors. Graduation outcomes emphasize diverse opportunities in intelligent systems and customer analytics.

Further Academic Progression: Students can pursue PhD programs in Data Science, Artificial Intelligence, or Applied Mathematics at Queen's or other UK institutions, building on the MSc's research project and modules like Frontiers in Data Analytics. Options include doctoral research in machine learning or big data, often with funding through university scholarships or industry collaborations.