Scientific Computing and Data Analysis (Financial Technology) Durham University

Overview

The MSc in Scientific Computing and Data Analysis (Financial Technology) at Durham University offers an in-depth exploration of the intersection between advanced computing techniques and financial markets. This programme is meticulously designed to equip students with the necessary skills to thrive in the rapidly evolving financial technology landscape. With a focus on practical applications, the course integrates three core strands: the foundational principles of computer science, the mathematical theories underpinning data analysis, and the implementation of these techniques in various specialisations, including Financial Technology.

Why Scientific Computing and Data Analysis (Financial Technology) at Durham University?

Durham University is renowned for its academic excellence and innovative research. The university's Computer Science Department is at the forefront of technological advancements, providing students with access to cutting-edge facilities and resources. The strong emphasis on research-led teaching ensures that students are not only learning theoretical concepts but also applying them in real-world scenarios. Additionally, the university maintains robust partnerships with industry leaders, enhancing career opportunities for graduates.

Tuition Fee Breakdown

The tuition fees for the MSc in Scientific Computing and Data Analysis (Financial Technology) are as follows:

• National students: £14,500 per year
• International students: £34,000 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The course structure is designed to provide a comprehensive understanding of both theoretical and practical aspects of scientific computing and financial technology. The core modules include:

• Introduction to Machine Learning and Statistics
• Introduction to Scientific and High Performance Computing
• Professional Skills
• Project
• Advanced Financial Technologies
• Financial Mathematics

Students also have the opportunity to select from optional modules that may include advanced statistical techniques, data acquisition, and performance modelling, allowing for a tailored educational experience.

Careers with Scientific Computing and Data Analysis (Financial Technology)

Graduates of this programme are well-prepared for a variety of roles in the financial services sector. Many alumni have successfully secured positions as software engineers, data analysts, and consultants in prestigious organisations such as investment banks, hedge funds, and technology firms. The programme's strong focus on practical skills ensures that students are equipped to meet the demands of employers across diverse industries.