A UK 2:1 honours degree, or its international equivalent, in informatics, artificial intelligence, cognitive science, computer science, electrical engineering, linguistics, mathematics, physics, or other numerate degree.
Competent programming skills are essential. During your degree you must have completed a programming course in at least one of the following: C/C++, Java, Python, R, Matlab, Haskell, ML.
During your degree you must have completed the equivalent to 60 credits of mathematics that have typically covered the following subjects/topics: calculus (differentiation and integration), linear algebra (vectors and multi-dimensional matrices), discrete mathematics and mathematical reasoning (e.g. induction and reasoning, graph theoretic models, proofs), and probability (concepts in discrete and continuous probabilities, Markov chains etc.)
(Revised 17/01/2020 to include details on programming skills and credits in Mathematics.)
For 2020 entry we accept the following English language qualifications at the grades specified*:
IELTS Academic: total 6.5 with at least 6.0 in each component.
TOEFL-iBT (including Special Home Edition): total 92 with at least 20 in each section. We do not accept TOEFL MyBest Score to meet our English language requirements.
PTE Academic: total 61 with at least 56 in each of the Communicative Skills scores.
CAE and CPE: total 176 with at least 169 in each paper.
Trinity ISE: ISE II with distinctions in all four components.
*(Revised 21 February 2020 to remove PTE Academic from 2021 entry requirements. Revised 21 April 2020 to include TOEFL-iBT Special Home Edition in 2020 and 2021 entry requirements.)
Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.
For 2021 entry we will accept the following English language qualifications at the grades specified*:
IELTS Academic: total 6.5 with at least 6.0 in each component. TOEFL-iBT (including Special Home Edition): total 92 with at least 20 in each section.We do not accept TOEFL MyBest Score to meet our English language requirements. CAE and CPE: total 176 with at least 169 in each paper. Trinity ISE: ISE II with distinctions in all four components.
This new programme will provides you with a critical and practical appreciation of how data, computing and artificial intelligence technologies can be used and developed to deliver value in organisations with finance, risk and decision-making related digitalisation from both technology and business perspectives.
The move towards digital organisations offers great potential for small and large, public and private enterprises. The University is in the UK's second largest financial centre after London and is leading cutting-edge, data-driven innovation to become the data capital of Europe.
This programme is taught by world class researchers and educators. It is based on full-time cross-disciplinary study and has strong links to existing centres of research excellence within three world-class academic Schools – the School of Informatics, Edinburgh Business School and the School of Mathematics.
This MSc consists of approximately seven months of taught courses across two semesters and up to four months of project work leading to a dissertation focused on both academic and real-world industry challenges.
It provides a unique blend of advanced technical courses, including finance-related sectors, and digital business skills with an emphasis on finance elements (minimum 30 credits) from Edinburgh Business School).
The programme provides you with unique interdisciplinary training. While the computing courses build up your technical skills, maths and finance related courses develop your ability to understand the finance system challenges associated with the development, implementation and exploitation of technical solutions.
Graduates will be equipped with the strong technology knowledge and background to keep up with developments in computing technologies and business awareness. Typical areas in which to pursue a career might include quant developer, financial system architect, application engineer, financial system consultant, software developer, and data scientist (in academia or industry), as well as financial system engineers of various kinds in IT firms, banks, and the investment and finance sectors, or in government and public sector positions.
