MSc Business Analytics

The MSc Business Analytics is a professionally accredited, one-year specialist programme for graduates with a substantial quantitative component, and those with demonstrable advanced quantitative skills. It will suit graduates or early career professionals aiming for careers in business analytics across sectors such as digital marketing, human resources, logistics, retail, finance, banking, insurance, healthcare, and agriculture.

Accredited by the Institute of Analytics (IoA), this programme aligns with the IoA’s mission to uphold the highest professional and ethical standards in data analytics, enhancing employability in a rapidly evolving industry. The programme is designed in collaboration with industry professionals from IBM, LV, and the UCL/IBM Industry Exchange Network. It offers students hands-on experience through projects addressing real-life managerial challenges, in partnership with organisations such as IBM, NHS, Barilla, and Bristol Airport, among others.

Students will gain a critical understanding of organisational, societal, and ethical issues in the use of Business Analytics, balancing innovation and competitiveness with public trust and corporate social responsibility. Projects include resource allocation optimisation, people analytics, customer segmentation and sentiment analysis, performance measurement in various sectors, healthcare workforce impact analysis, and automation of renewable energy systems.

The programme covers:

• Data preparation skills, including data identification, extraction, and cleaning
• Statistical and machine learning techniques for data mining and predictive analytics
• Formulation and execution of statistical and mathematical models for business decision optimisation
• Visualisation, interpretation, and communication of statistical analysis results

Students will primarily use Python and software like Lingo for ad-hoc data analytics. Guidance will be provided on achieving professional accreditation from the UK's leading Operational Research Society and other affiliated organisations such as the Alliance of Data Science Professionals.

To further enhance students' analytics profiles and work readiness, students might engage with the Professional Liaison Network (PLN) on consulting projects, providing experience with significant organisations. Alumni panel discussions, virtual industry panels, guest lectures from industry experts, career development workshops, and technology workshops on tools like PowerBI, @RISK, and SQL are integral components designed to keep students updated with the latest industry practices. Mentorship programmes are also being established to connect students with alumni and industry experts.