Business Analytics MSc

Core modules:

Fundamentals of Business and Management

In this module, you will build a strong foundation in business and management concepts, focusing on integrating analytics into decision-making. You will explore key areas like finance, marketing, operations, and human resources (HR) learning how data can enhance strategies, improve efficiency, and create a competitive edge. You will also dive into key frameworks on how firms compete and outperform competitors  using analytics.

Through case studies and hands-on projects, you will  apply analytics to optimise performance and uncover new opportunities. You will also learn how analytics drives both internal operations and external strategies, improving productivity and market insights. Finally, you will discover how leadership and change management foster a data-driven culture. By the end, you will be equipped to use analytics in real business scenarios, preparing you for success in today's data-driven world.

15 credits

Probability and Statistics

This module provides a practical and engaging introduction to probability and statistics, equipping you with essential skills for data analysis. You will learn key concepts such as probability theory, statistical inference, hypothesis testing, and basic linear models—fundamental tools for making sense of data.

Through hands-on exercises and real-world applications, you will develop the ability to interpret data, draw meaningful conclusions, and make informed decisions. This module also covers experimental design, helping you understand how to structure research to ensure reliable and valid results.By the end of this module, you will have the confidence to apply statistical techniques in business, science, or everyday problem-solving, laying a strong foundation for more advanced analytics.

15 credits

Mathematical Modelling for Decision-Making

In this module, you will learn key mathematical modeling techniques used in decision-making, essential in business analytics. These techniques are widely applied in industries like finance, supply chain management, marketing, and operations to solve problems related to resource allocation, production scheduling, and logistics.

You will learn continuous and linear optimisation, linear programming, the formulation of optimisation problems and the  interpretation of solutions in a business context, using general optimisation solvers to efficiently solve large-scale problems. You will also explore integer and binary programming, quadratic programming and network design and optimisation.

Through hands-on exercises and case studies, you will apply these techniques to real business analytics problems, learning to use solvers for efficient problem-solving. By the end of the module, you will be prepared for more advanced topics in the second semester.

15 credits

Programming for Business Analytics

This module introduces programming languages essential for business analytics, with a strong focus on Python and its ability to integrate with tools like Excel, R, SQL, and commercial solvers. Rather than a theoretical coding course, this module takes a hands-on, application-driven approach, demonstrating how programming supports real-world business analytics.

Through interactive sessions and practical exercises, you will learn: Fundamental programming concepts for data manipulation and analysis. How to write clean, efficient, and well-documented code following best practices. Seamless integration of Python with Excel, SQL databases, and other analytical tools. Application of programming in business scenarios, such as financial modeling, marketing analytics, and operational optimisation.

Using a blended learning approach, the module combines theory, coding exercises, and real-world case studies to help you gain confidence in applying programming to business problems. By the end, you will be equipped with the skills to develop data-driven solutions, automate workflows, and enhance decision-making in a business environment.

15 credits

Advanced Analytics: Econometrics and Forecasting

Based on the foundations laid in the first semester through the Probability and Statistics module, you will have a structured approach to data analysis, focusing on econometrics and forecasting. You will also develop the ability to predict future trends and outcomes, equipping you to create solutions that optimise resource allocation, forecast demand, or guide strategic planning. You will gain hands-on experience applying these methods to real-world scenarios, enhancing your ability to make data-driven predictions and informed decisions.

15 credits

Data Mining and Visualisation

This course equips you with the skills to extract valuable insights from unstructured data using advanced data mining techniques and effective data visualisation methods.You will learn how to identify meaningful patterns, trends, and relationships within large datasets, applying machine learning algorithms and statistical techniques to real-world business problems. 

A key focus of this module is data visualisation, where you will develop hands-on expertise in Tableau, one of the leading tools for interactive and dynamic data storytelling. You will explore best practices for designing compelling visualisations, dashboards, and reports that effectively communicate data-driven findings to business stakeholders.

15 credits

Decision Support Systems

This module equips you with the tools to optimise operations and improve efficiency in complex environments. Building on the foundations of the Mathematical Modelling for Decision-Making  module, you will tackle real-world challenges like vehicle routing, scheduling, and supply chain design. You will also explore tools that support spatial decision-making, gaining hands-on experience with industry-relevant decision support tools. By the end of the module, you will be able to apply these techniques to solve logistical and operational problems across various sectors.

15 credits

Database Management and Governance

In this module, you will explore the foundational concepts of database management and data structures, focusing on widely used technologies and techniques in business analytics. A core aspect of the module is mastering Structured Query Language (SQL), an essential tool for querying, managing, and manipulating databases efficiently. Through hands-on exercises, you will develop practical skills in designing and optimising databases to support data-driven decision-making. Beyond technical skills, this module places a strong emphasis on data governance and ethics. You will critically examine the legal, ethical, and regulatory frameworks that shape data management, including GDPR, compliance standards, and responsible AI. By understanding key principles such as data privacy, security, and accountability, you will learn how to navigate complex ethical dilemmas and ensure responsible data practices in professional settings. By the end of the module, you will not only be proficient in SQL and database management but also equipped with the knowledge to make informed, ethical decisions in handling data within organizations. These skills will be crucial in ensuring trust, compliance, and sustainability in business analytics.

15 credits

Business Analytics in Practice

This module equips you with the skills to analyse data and drive business decisions. Through real-world case studies and hands-on projects, you will tackle challenges in finance, marketing, supply chains, manufacturing and customer analytics.

You will learn to apply statistical models, data visualisation, and machine learning techniques to extract insights and predict outcomes. Beyond technical skills, the module emphasises critical thinking, problem-solving, and effective communication—ensuring you can present complex findings in a clear, business-relevant way.

With industry case studies, collaborative projects, and expert insights, this module prepares you to leverage analytics for strategic decision-making in any organisation.

15 credits

Capstone Project for Business Analytics

This capstone project is an industry-focused research project desirably conducted in collaboration with business partners. You will apply your analytical skills to solve practical business problems and gain valuable real-world experience.

45 credits