• Ross University School of Veterinary Medicine Featured Masters Courses
  • Jacobs University Bremen gGmbH Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
  • Anglia Ruskin University Featured Masters Courses
  • Swansea University Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
  • Goldsmiths, University of London Featured Masters Courses
  • University of Southampton Featured Masters Courses
King’s College London Featured Masters Courses
Bocconi University Featured Masters Courses
Queen Mary University of London Featured Masters Courses
FindA University Ltd Featured Masters Courses
University of Pennsylvania Featured Masters Courses
"probabilities"×
0 miles

Masters Degrees (Probabilities)

We have 3 Masters Degrees (Probabilities)

  • "probabilities" ×
  • clear all
Showing 1 to 3 of 3
Order by 
This programme is now closed but you may want to consider other courses such as the . Mathematics MSc. . . Read more

This programme is now closed but you may want to consider other courses such as the Mathematics MSc

The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.

  • A rigorous approach to quantitative finance taught entirely by the Department of Mathematics.
  • In-depth coverage of the skills needed for working in the financial, actuarial or related industry: probability theory, optimisation, statistics and computer implementation.
  • Unrivalled facilities in central London with City of London's financial centre close by, and with access to live market data in our Bloomberg Data Laboratory.
  • Flexible study programme offering the opportunity to study part-time.
  • King’s is a member of the London Graduate School in Mathematical Finance which provides advanced courses for students who wish to push beyond the MSc core syllabus.
  • Lecturers on the programme have extensive experience in consulting and work for financial companies and institutions such as Bank of Finland, Commerzbank, Deutsche Bank, Goldman Sachs, ION Trading, Standard Chartered Bank and Winton Capital Management.

Description

Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management

Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.

Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.

The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.

Bloomberg terminal laboratory

King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.

You will use the Bloomberg terminals to:

  • Gain an intuition for the conduct of real financial markets
  • Develop potential investment strategies
  • Experience using real-world investment and risk management software and obtain data for research.

The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.

We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.

Course purpose

This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.

Course format and assessment

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Average per week: Three hours for 11 weeks per each 15 credit module.

You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.  

Career destinations

Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.



Read less
Programme description. This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world. Read more

Programme description

This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world.

Our research draws on neuroscience, cognitive science, linguistics, computer science, mathematics, statistics and psychology to span knowledge representation and reasoning, the study of brain processes and artificial learning systems, computer vision, mobile and assembly robotics, music perception and visualisation.

We aim to give you practical knowledge in the design and construction of intelligent systems so you can apply your skills in a variety of career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

Compulsory courses:

  • Informatics Research Review
  • Informatics Research Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses:

  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Processing

You can choose from a variety of optional courses including:

  • Advanced Vision
  • Algorithmic Game Theory and Its Applications
  • Computer Animation and Visualisation
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Robotics: Science and Systems
  • Human-Computer Interaction
  • Software Architecture, Process and Management
  • Text Technologies for Data Science
  • Computational Cognitive Neuroscience

Career opportunities

Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to spacecraft control.



Read less
Programme description. This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet. Read more

Programme description

This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet.

You will gain a solid foundation in theoretical understanding and learn a wide variety of practical techniques that you could use in varied career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses. The specialist areas are:

  • Analytical and Scientific Databases
  • Computer Systems, Software Engineering, and High Performance Computing
  • Programming Languages
  • Theoretical Computer Science
  • Cyber Security and Privacy

Compulsory courses:

  • Informatics Research Review
  • Informatics Research Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

There are more than 50 optional courses to choose from, such as:

  • Machine Learning and Pattern Recognition
  • Probabilistic Modelling and Reasoning
  • Extreme Computing
  • Bioinformatics
  • Computer Graphics
  • Computer Networking
  • Human-Computer Interaction
  • Parallel Architectures
  • Parallel Programming Languages and Systems
  • Software Architecture, Process and Management
  • Algorithmic Game Theory and its Applications
  • Computer Algebra
  • Computational Complexity

Career opportunities

Through this programme you will develop specialist, advanced skills in the development, construction and management of advanced computer systems.

You will gain practical experience and a thorough theoretical understanding of the field making you attractive to a wide range of employers or preparing you for further academic study.



Read less

  • 1
Show 10 15 30 per page



Cookie Policy    X