A minimum of a second class honours degree or equivalent. Applicants without these formal qualifications but with significant appropriate/relevant work/life experience are encouraged to apply.
Months of entry
s the modern financial industry increasingly turns to big data to inform investment decisions, there is a growing demand for professionals with a specialisation in data analytics. This course equips you with data analysis skills that are in short supply, including algorithmic trading, use of machine learning, and artificial intelligence.
As you study, you’ll develop core skills in finance, investments and data analytics – all of which can be applied in a final dissertation on a finance-related topic of your choice. You’ll also be taught how to use programming languages (e.g. Python, R) to analyse data and get a thorough understanding of core financial theory and investment practices. In addition, you'll have the opportunity to use professional financial databases, such as Bloomberg, Eikon and S&P Capital IQ.
Other features of the course include the Amplify Trading Boot Camp, where you can get first-hand experience of real-world trading, and the Student Managed Investment Fund, which provides experience of managing actual funds through targeted investments. All these features help to enhance employability, give you practical skills, and play a part in a world-leading student experience.
Information for international students
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.0 with 5.5 minimum in each skill
- Cambridge C2 Proficiency (CPE) 180 with minimum 162 in each skill
- Cambridge C1 Advanced (CAE) 169 with minimum of 162 in each skill
- Pearson Test of English (Academic): 54 with 51 in each component
- IBT TOEFL: 80 with no subtest less than 17
For more information on ways that you can meet our English language requirements, including options to waive the requirement, please read our information on English language requirements.
Fees and funding
Qualification, course duration and attendance options
- full time12 months
- Campus-based learningis available for this qualification
Course contact details
- Dr Konstantinos Gavriilidis