Program Overview

MSc Data Analytics

The MSc Data Analytics is designed to create rounded data analytics problem-solvers. The course focuses on the uses of data analytics techniques within business contexts, making informed decisions about appropriate technology to extract knowledge from data and understanding the theoretical principles by which such technology operates.

Key Facts

• Start date: September
• Accreditation: AACSB, EQUIS & AMBA
• Application deadline: Applications are accepted throughout the year
• Study mode and duration: MSc: 12 months full-time, 24 months part-time

Course Description

On our MSc Data Analytics programme, you'll learn from experts across three disciplines - Management Science, Computer & Information Sciences, and Mathematics & Statistics - providing a uniquely broad foundation in data analytics. You'll apply your skills to industry-led case studies, gaining practical experience and a portfolio of evidence to showcase to employers. You'll access the latest research in machine learning and AI for business, equipping you with cutting-edge knowledge and tools for data-driven decision-making. You'll choose from a range of optional classes for specialisation.

Course Content

• Core classes
  • Big Data Fundamentals (10 credits)
  • Foundations of Statistics (10 Credits)
  • Data Analytics in R (20 credits)
  • Business & Decision Modelling
  • Optimisation for Analytics
  • Data Analytics in Practice
• Elective classes
  • Department of Computer & Information Sciences
    • Database Fundamentals (10 credits)
    • Evolutionary Computation for Finance 1
    • Evolutionary Computation for Finance 2
    • Legal, Ethical & Professional Issues for the Information Society
    • Fundamentals of Machine Learning for Data Analytics (10 credits)
    • Machine Learning for Data Analytics
  • Department of Mathematics & Statistics
    • Financial Econometrics (10 credits)
    • Bayesian Spatial Statistics (20 credits)
    • Statistical Machine Learning (10 Credits)
    • Data Dashboards with R Shiny (10 Credits)
  • Department of Management Science
    • Stochastic Modelling for Analytics
    • Business Simulation Modelling
    • Risk Analysis & Management (10 credits)
    • Business Information Systems

Learning & Teaching

Core and elective classes will be taught across two semesters running from September to December and January to March. Classes will be taught through a combination of lectures, tutorials, hands-on software sessions, projects, and case studies. The dissertation is undertaken during the summer months.

Assessment

Classes are assessed by various methods, including written assignments, exams, practical team projects, presentations, and individual projects. Exams will take place at the end of each semester in December and April/May.

Facilities

Strathclyde Business School (SBS) is one of a few triple-accredited business schools in the world and is one of the largest of its kind in Europe. SBS was also selected as the Business School of the Year in Times Higher Education (THE) Awards 2016.

Entry Requirements

• Academic requirements: Minimum second-class Honours degree, or overseas equivalent, in mathematics, the natural sciences, engineering, economics/finance, or other degrees with demonstrated numerical/quantitative subjects.
• English language requirements: Students whose first language is not English must have a minimum of 6.5 IELTS score, with no individual score lower than 5.5.

Fees & Funding

• Scotland: £14,250
• England, Wales & Northern Ireland: £14,250
• Republic of Ireland: Same as England, Wales & Northern Ireland
• International: £31,100
• Additional costs: Course materials, placements & field trips, international students' associated visa and immigration costs.

Careers

The aim of the course is to develop graduates who can use data analytics technology, understand the statistical principles behind the technologies, and understand how to apply these technologies to solve business problems. Graduates will be able to bridge the various knowledge domains that are relevant for tackling data analytics problems as well as being able to identify emerging themes and directions within data analytics. Examples of graduate employers and job roles include:

• Software Development Engineer - Machine Learning at RBS
• Junior Data Scientist at V.Group
• Data Scientist at Solita Scandinavia
• Business Analyst at Scottish Power
• IT Graduate at Scottish Power

Available Scholarships

Take a look at our Business School scholarships.