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The MSc Data Analytics at the University of Strathclyde is a 12-month full-time or 24-month part-time program jointly delivered by the Departments of Management Science, Mathematics & Statistics, and Computer & Information Sciences.
Based in the triple-accredited Strathclyde Business School (AACSB, EQUIS, AMBA), the program offers a comprehensive blend of theoretical foundations, hands-on practice, and strong industrial engagement.
Course Overview:
Core:
Data Analytics in R
Business and Decision Modelling
Foundations of Statistics
Big Data Fundamentals
Optimisation for Analytics
Electives (select at least four credits):
Machine Learning for Data Analytics
Database Fundamentals
Financial Econometrics
Bayesian Spatial Statistics
Legal, Ethical & Professional Issues for Information Society
Business Simulation Modelling
Summer Dissertation Project
Teaching: Lectures, tutorials, hands-on software labs, projects, and case studies.
Assessment: Written assignments, exams, group projects, presentations, and individual projects.
Data Analytics in Practice Module: Hands-on, year-long project working directly with external organisations on complex, real-world business challenges.
Industry-Led Case Studies: Guest speakers and industry-led case studies provide practical insights and networking opportunities.
Dissertation Project: Option to conduct research in collaboration with client organisations on live data analytics problems.
Elective Specialisation: Customisable study path with options from at least two departments to gain cross-disciplinary expertise.
Facilities: Access to state-of-the-art software, computing labs, and participation in the Strathclyde Business Network and Glasgow Business Summit.
Career Prospects: Graduates are well-positioned for roles in data science, analytics, machine learning, and business intelligence across sectors such as finance, consulting, retail, and technology.
Industry Engagement: Strong employer partnerships and project-based learning enhance career readiness.
Further Study: Graduates are also well-prepared for PhD and research-based opportunities.
Part time studies available; 24 monthsTriple accredited by AACSB, EQUIS and AMBAIELTS: 6.5 score, with no individual score lower than 5.5. TOEFL: 73 overall, with a minimum of 18 in the writing sectionScholarships availableYour personal details, academic qualifications (predicted works too), a personal statement, evidence of your English language skills (with relevant qualifications), a reference and employment history are required for applications.Data ScientistData AnalystMachine Learning EngineerBusiness Intelligence AnalystData EngineerOperations Research AnalystStatisticianQuantitative AnalystBig Data EngineerData Visualisation Specialist
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University of Strathclyde
