MSc Economics & Data Analytics - Economía y Análisis de Datos

The MSc Economics and Data Analytics gives you the economic insight, analytical expertise and computational skills to solve real-world business challenges. Through this program, you will learn how to turn complex data into strategic decisions that drive impact across global organizations.

Academic requirements:

A minimum of a 2:2 Honors degree from a UK or recognized international university or another equivalent international qualification; or
An acceptable professional qualification equivalent such as the CMI, CIM, ACCA, CIMA, at level 6 or above
A grade C/4 in English Language and Maths
Proof of English level:

TOEFL score 93/4.5 (as of Jan 2026) (internet-based), 238 (computer-based); IELTS 6.5 with at least a 5.5 minimum in each section; IELTS 6.5 with at least a 5.5 minimum in each section; CAE C1 with a minimum score of 176; minimum PTE-A of 59; native speaker of English or equivalent.

Term 1

Macroeconomics in a Global Context
This course aims to provide the student with an understanding of the global nature of the activity of the modern economy and its effect on the macroeconomic policy of states. The long-standing tendency for states’ economic operations to be treated in isolation from one another has led to a continuous neglect of the often overwhelming contextual factors in the formulation of theory, such as the importance of the sustainability agenda worldwide. The course presents an integrated perspective of the key dimensions of global economic activity, rather than the hybrid treatment of the past conceptions of separable economic categories. The course recognizes the interpenetration of global economic activities between the key actors.

Applied Microeconomics
This course enables students to acquire a systematic understanding and knowledge of applied microeconomics, focusing on how economic principles and models can be applied to understand and address real-world issues and policy debates. Emphasis is placed on the use of empirical evidence and data-driven analysis to critically evaluate market outcomes, the behavior of consumers and firms, competitive behavior, market failure and the role of government intervention in the economy. This allows students to develop an appreciation of issues and problems facing policy makers and a capacity to apply economic reasoning in a critical manner.

Term 2

Data Analysis
This course provides an introduction to research methods used in the social sciences and particularly in economics research. The focus is on the use of statistical methods and the course will cover different types of datasets, how to use the data and different ways to visualize the data. Students will gain skills in research design and how to apply data to answer questions that arise in economic, policy or other social science research. Through this course, students will learn and gain an understanding of how to interpret regression analysis and will be able to discuss and defend their analysis.

Econometrics
Students will gain foundational knowledge of econometric principles and methods, with a focus on applying data analysis techniques to solve real-world economic problems. The course will balance theoretical understanding with practical data handling skills and focus on real-world applications. By the end of this course, students will be prepared to apply econometric analysis within economic research, business and policy contexts, providing a foundation for more advanced quantitative studies.

Term 3

Data Mining & Machine Learning
This course provides an appreciation of data mining and machine learning fundamental concepts, algorithms and processes. It covers machine learning algorithms and data mining techniques for data analysis, pattern mining, clustering, classification and regression. It equips the students with practical skills in applying these data techniques in real-world analytics problems.

Modeling of Data & Predictive Analytics
This course begins with a foundational level of mathematics and Python. Mathematics will be primarily of an applied nature, including linear algebra (matrices). Python will begin with the handling of data and simple functions. After this, students will explore the use of Python to acquire data via public API, manipulation of data and the running of a predictive model, for example, Long Short Term Memory (LSTM). At the same time as establishing Python skills, the course will provide students with a solid grounding in the application of data for business and the use of analytics to create commercial value.

Economic Data Strategist
Guides clients on financial decisions, offers tailored banking solutions and enhances wealth growth.

Analytics Consultant
Transforms complex data into insights, advises on analytics solutions and boosts performance outcomes.

Pricing & Revenue Optimization Analyst
Develops pricing models, analyzes
demand patterns and maximizes revenue through strategic insights.

Economics and Market Intelligence Analyst
Monitors economic indicators, evaluates market dynamics and delivers actionable intelligence.

Quantitative Strategy Analyst
Builds data-driven models, analyzes
financial and economic variables and shapes strategic business decisions.

Critically evaluate methodologies and adapt a variety of advanced quantitative and economic techniques, to be able to effectively propose solutions to real economic problems.
Formulate, conceptualize and frame economics and data problems and questions so as to propose feasible solutions.
Critically acquire and analyze data within micro and macroeconomic contexts.
Be able to use a variety of data tools (e.g., Python, Jupyter Notebook, R) to manipulate data and perform appropriate data analysis.
Generate inferences and conclusions based on data analysis.