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The MSc Big Data at the University of Stirling is an advanced program that equips students to collect, manage, and analyse large, fast-moving datasets using modern big data technologies.
The course is specifically designed for students from non-computing backgrounds and focuses on both the technology of big data and the science of data analytics. With hands-on training in tools such as SQL/NoSQL databases, Hadoop, Python, R, and machine learning, students develop practical skills aligned with industry needs.
The program offers strong industry connections, guest lectures, and opportunities for internships and live commercial projects.
Course overview
Core modules: Representing and Manipulating Data, Commercial and Scientific Applications, Statistics and Networks Analysis in Data Science, Machine Learning, Cluster Computing, Relational and non-Relational Databases, Dissertation, Professional Doctorate First Stage
Teaching: Delivered through practical labs, lectures, seminars, tutorials, project-based learning, and guest industry lectures.
Assessment: Assessed via practical coursework, exams, and a major industry-relevant project.
Hands-on Labs and Workshops: Practical sessions focused on mastering big data technologies like Hadoop, Python, and SQL through supervised lab work.
Project-Based Learning: Real-world projects allow students to design and build big data solutions using datasets relevant to current industry problems.
Industry-Linked Research Projects: Students can work on live commercial projects with organisations like Fishvet Group and Sainsbury’s Bank, applying their skills to genuine business challenges.
Guest Lectures from Industry Leaders: Regular seminars delivered by experts from companies like MongoDB, SkyScanner, and HSBC provide direct insights into the big data landscape.
Internship and Industry Collaboration Opportunities: The program includes options to gain professional experience through internships or collaborative projects with key employers.
Flexible Study Options: Offers full-time, part-time, and online study pathways, making the course accessible to both local and international students with varied commitments.
Industry-Informed Curriculum: Course content and assessments are developed in consultation with industry partners to ensure alignment with employer needs.
Career Workshops and Networking Events: Students can attend professional development sessions and networking opportunities to connect with potential employers.
Supportive Learning Environment: Benefit from personalised support, small group teaching, and expert academic supervision throughout the course.
Access to Library and Digital Resources: Full access to Stirling’s digital learning platforms, specialist software, and an extensive library to support research and project work.
The MSc Big Data at Stirling prepares graduates for high-demand roles in leading global companies across technology, finance, healthcare, and government sectors.
High Graduate Employability: Alumni have secured positions at companies such as Lloyds Banking Group, EasyJet Commercial, Competition and Markets Authority, Scottish Prison Service, Abbott, and AXS Europe.
In-Demand Roles: Graduates typically progress into roles including Lead Data Scientist, Senior Data Engineer, Big Data Engineer, HR Analytics Manager, Full Stack Developer, Data Analyst, and Director of Data Science.
PhD Opportunities: Graduates may pursue doctoral research in Big Data, Data Science, or Artificial Intelligence at Stirling or other leading universities.
Specialist Postgraduate Study: Students can progress to advanced MSc programs in areas such as Machine Learning, Business Analytics, or Advanced Computing for further technical specialisation.
Part time studies available; 2 yearsScholarships availableA minimum of a second-class honours degree (2.1 preferred) or equivalent in any discipline. Applicants without these formal qualifications but with significant appropriate work experience are encouraged to apply.This course is intended for students without a background in computing. If you have a degree in computing, or a closely related subject, or equivalent experience, then you are strongly encouraged to take the Advanced Computing and AI course instead.IELTS Academic or UKVI: 6.0 with a minimum of 5.5 in each sub-skill.TOEFL iBT: 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing.Your 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.Two Intakes: January and SeptemberLead Data ScientistSenior Data EngineerBig Data EngineerSenior Technology AdviserHR Analytics ManagerFull Stack DeveloperData ScientistData AnalystDirector of Data ScienceData Engineer
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University of Stirling
