MSc - Master of Science
Finance and Machine Learning MSc
- Provides a strong background in finance
- Grounding in machine learning methods and how they are used in finance through cutting-edge curriculum
- The knowledge to implement machine learning tools using Python
- A learning environment that encourages the development of systematic and independent thought and learning
- A methodical knowledge of quantitative methods so that you will have the skills necessary to undertake quantitative analyses of relevant problems
School of Economics and Finance
- Around 1,000 master’s students from all over the world
- Teaching by research-active academics as well as visiting city professionals
- Wide range of elective modules
- Wide range of optional short modules (on programming languages, trading platforms such as Bloomberg, etc.)
Campus and Facilities
- Close to London’s financial districts (City of London and Canary Wharf)
- On-site accommodation
- State of the art building
- State-of-the art computer labs with mathematical and trading software (eg Reuters and Bloomberg)
The programme will be delivered at the university's Mile End campus.
The programme consists of four compulsory modules in semester A as well as two compulsory modules and two electives in semester B.
During the summer period, supervised by an academic member of staff, students will have to complete a dissertation project. Students can choose between the 45 credit dissertation or 15 credit research project. The latter will allow them to choose 30 credits of electives in the 3rd semester.
Students will also be offered a two-week pre-sessional course whose aim is to introduce students without a strong quantitative background to the necessary mathematics and statistical concepts.
During the summer period, supervised by an academic member of staff, students will have to complete a dissertation project.
Students can choose between the 45 credit dissertation or 15 credit research project. It is assessed, on the basis of the individual literature review main report, initially by the supervisor, then a second examiner and then by the External Examiner and the full Examination Board.
Taught by research-active academics as well as visiting professionals
The learning outcomes for the programme are delivered by a range of modules across the programme.
Teaching and learning is mainly via expert lectures and seminars (some are to be delivered weekly others on alternative weeks).
Teaching and learning strategies vary from module to module.
Wide range of economics careers, especially as research economist in the public sector, international institutions, economic consulting.
Further studies in MRes or PhD (best students often continue onto MRes within our school).
Our dedicated careers team offers students one-on-one appointments, support with job applications, practice interviews, information about internship opportunities and employability events.
There are a number of ways you can fund your postgraduate degree.
- Scholarships and bursaries
- Postgraduate loans (UK students)
- Country-specific scholarships for international students
- United States
- Antigua & Barbuda
- Bosnia and Herzegovina
- Burkina Faso
- Cabo Verde
- Central African Republic
- Congo (Democratic Republic)
- Costa Rica
- Czech Republic
- Dominican Republic
- East Timor
- El Salvador
- Equatorial Guinea
- Hong Kong
- Ivory Coast
- Korea DPR (North Korea)
- Marshall Islands
- New Zealand
- Northern Ireland
- Palestinian Authority
- Papua New Guinea
- Puerto Rico
- Republic of Ireland
- San Marino
- Sao Tome and Principe
- Saudi Arabia
- Sierra Leone
- Solomon Islands
- South Africa
- South Korea
- South Sudan
- Sri Lanka
- St Vincent
- St. Kitts & Nevis
- St. Lucia
- Trinidad & Tobago
- United Kingdom
- Vatican City
- Western Samoa
£ 24,950per year
Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.
University League Table
Queen Mary University of London, Admissions and Recruitment Office, Mile End Road, Tower Hamlets, E1 4NS, England
19th out of 103 8
37th out of 110 3
Entry standards/ Max 220160 73%
Graduate prospects/ Max 10082 82%
Student satisfaction/ Max 53.82 76%
Entry standards/ Max 236167 70%
Graduate prospects/ Max 10082 82%
Student satisfaction/ Max 53.67 73%