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伦敦大学皇家霍洛威学院-计算金融硕士Computational Finance MSc(硕士)

伦敦大学皇家霍洛威学院-计算金融硕士Computational Finance MSc(硕士)

上课方式:直播,面授
班级类型:小班
上课时段:白天班,晚班
价       格:¥询价

伦敦大学皇家霍洛威学院-计算金融硕士Computational Finance MSc(硕士)课程详情

  • 专业概况
  • 所属院系
  • 中国学生入学要求
  • 课程信息

专业概况

在这里学什么?

The course

This course, offered by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling, which are demanded for jobs in asset structuring, product pricing as well as risk management.

Skills that you will acquire include the ability to:

  • analyse, critically evaluate, and apply methods of computational finance to practical problems, including pricing of derivatives and risk assessment
  • analyse and critically evaluate methods and general principles of computational finance and their applicability to specific problems
  • work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks
  • analyse and critically evaluate applicability of machine learning algorithms to problems in finance
  • implement methods of computational finance and machine learning using object-oriented programming languages and modern data management systems
  • work with software packages such as MATLAB and R
  • work with Relational Database Systems and SQL

Teaching & assessment

Teaching is organised in terms of 11 weeks each. Examinations are taken in April/May of each academic year, except for Data Analysis for which the exam is in January. The individual project is taken over 12 weeks during the Summer.

A weekly seminar series runs in parallel with the academic programme, which includes talks by professionals in a variety of application areas as well as workshops that will train you to find a placement or a job and lead a successful career.

Assessment is carried out by a variety of methods including coursework, small group projects, and examinations, the proportions of which vary according to the nature of the modules.

Your future career

Demand for computational finance analysts is buoyant, in the UK and worldwide, with salaries much higher than other IT professions and at least double the UK average full-time wage. Study Computational Finance at Royal Holloway, University of London and you'll graduate with excellent employability prospects in a range of fields.

Our proximity to the M4 corridor also known as 'England’s Silicon Valley' - provides excellent networking opportunities with some of the country’s top technology institutions. We bring several companies to our campus throughout the year, both for fairs and for delivering advanced topics seminars, which are an excellent opportunity to learn about what they do and discuss possible placements or jobs.

Our graduates enter into successful careers in academia or in companies or organisations operating in highly competitive areas.

In addition to the support provided by The Careers and Employability Service, the department has a dedicated administrator and an academic who coordinates and oversees placements and job opportunities.

  • Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
  • Together with our on-site Careers and Employability Service, we run one-to-one coaching sessions and workshops, helping you to find a placement or job and lead a successful career.

所属院系

进入哪个院系学习? Computer Science

中国学生入学要求

为来自中国的学生设计 Students who have successfully completed a Bachelor degree (Xueshi) in an appropriate subject with good grades/GPA and at a reputable university will be considered for entry to a Royal Holloway Master's degree programme. Exact requirements will depend upon the programme they are applying for and the university they have graduated from, but most departments will ask for a minimum of 70-80% or a GPA of between 2.8-3.2/4.0. IELTS: 6.5 overall. No subscore lower than 6.0.

课程信息

学制:全日制(1 年)

学费:£21,500.00 (¥ 194,143) /年

开学时间:2022九月

申请截止日期:

留学地点:Royal Holloway, University of LondonEgham,Surrey,TW20 0EX, England

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