Overview

The extraction of actionable insights from vast and complex datasets relies on the foundational principles of advanced mathematical modeling and statistical theory. Students enrolled in BSc (Hons) Mathematics with Data Science at City St George's, University of London gain a rigorous grounding in pure and applied mathematics alongside specialized expertise in modern data analysis and computational techniques. The curriculum balances abstract mathematical reasoning with practical data science applications, benefiting from research-led instruction, technical computing facilities, and proximity to London's commercial technology and financial hubs. Learners explore core mathematical disciplines such as calculus, linear algebra, and probability, while mastering practical computing tools for data visualization, machine learning, and predictive modeling. Hands-on laboratory sessions and individual projects ensure that students learn to apply mathematical rigor to real-world data processing challenges. This degree is ideal for quantitative thinkers and analytical problem-solvers who wish to bridge abstract mathematics and data-driven technology. Graduates emerge with strong numerical fluency, programming skills, and versatile analytical capabilities.

What You'll Learn

Core pure and applied mathematics including multivariable calculus, linear algebra, and differential equations

Probability theory, mathematical statistics, hypothesis testing, and statistical modeling techniques

Data structures, algorithms, and high-level programming languages for mathematical computation and data manipulation

Machine learning algorithms, predictive analytics, data visualization techniques, and pattern recognition

Big data frameworks, database management systems, and computational methods for large-scale data analysis

Learning Outcomes

Graduates of this program will possess a comprehensive understanding of mathematical structures and statistical methodologies applied across diverse computational and data-driven contexts. Students develop the ability to critically analyze complex quantitative problems, formulate rigorous mathematical models, and evaluate the validity of data analytics outputs. Practical programming assignments and laboratory exercises equip learners with hands-on skills in data processing, statistical computing, and machine learning algorithm implementation. The curriculum provides opportunities to specialize in advanced mathematical fields or applied data science topics, allowing students to tailor their expertise to specific career interests. Ultimately, participants graduate with the mathematical precision, computational proficiency, and critical analytical skills required to address complex data challenges across science, finance, and technology sectors.