About the Bayes London Summer School
Duration: Three weeks starting from Monday 4th July until Friday 22nd July 2022
The Bayes London Summer School is your chance to study a credit-bearing module and enjoy the best of London as a global destination. The Bayes Summer School courses are taught in an intensive block over a period of three weeks and each module on the programme is equivalent to 10 UK / 5 ECTS credits.
Over three weeks you’ll learn from Bayes lecturers who are experts in their chosen fields. Many have experience working in the finance industry or leadership and entrepreneurship which means that you gain valuable real-world insights from academics who have actually worked on trading floors, at hedge funds and in corporate advisory teams.
Enrolling in Summer School will allow ambitious students to enhance their qualifications and test out life at in business school environment, while making the most of what London has to offer. The academic schedule is enriched by a social programme, careers support and networking events, giving you the chance to explore London and build both your CV and contacts.
London is an exciting and cosmopolitan place to study as well as being on the doorstep of many Fortune 500 companies.
Who is the course for?
The Summer School is open to current undergraduates, graduates and postgraduates of any discipline who want to gain an introduction to business or financial concepts, or further develop their understanding of particular areas of finance.
Our intensive modules are designed to boost your skills in specific areas of finance. Students can acquire key financial and managerial skills on introductory modules covering finance and quantitative methods, international accounting standards, international trade and shipping markets, entrepreneurship, leadership and organisation.
This is ideal if you have no previous exposure to formal training or experience in accounting, finance and management.
You can also study specialist modules including investment management, financial engineering, mergers and acquisitions, big data and machine learning. To enrol on these modules, you should have some previous academic or practical exposure to finance and management.