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伦敦国王学院计算金融专业

Computational Finance

专业排名

51

学制

1年

学费

40000.00英镑/年

雅思

7

主页 排名

专业介绍

The Computational Finance MSc will introduce students to the computational methods that are widely used by practitioners and financial institutions in today’s markets. This course will provide students with a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics and agent-based modelling. These techniques will be used to understand financial ma

移民相关

移民专业:否

就业前景

可从事的工作:网络安全公司、一般软件咨询公司、专业软件开发企业和大型机构(金融、电信和公共部门)的信息技术部门

如何申请

个人陈述:750字 A personal statement is required. You must answer the following three questions on the application form: Why are you applying for this specific programme, and how does it fit with your future plans? (max 250 words) How does your experience and education make you a suitable candidate for this programme? (max 250 words) Please briefly outline the contents of 2-3 of the most advanced pure mathematics modules you have taken/are currently taking, which might include an undergraduate project/dissertation. (max 250 words)

推荐信:1

简历:可选

申请费:130

申请截止日期:44645

测试申请录取成功率

采用最科学的人工智能算法,已为23127位学生申请到dream school,成功率96.33%。
免费测试

入学要求

专业领域:

1 计算机科学

2 quantitative相关类专业如数学、统计学,物理、Natural Science,电子工程,General Engineering,运筹学。

先修科目:【basic mathematics知识特别是在微积分、三角学、线性代数、向量和矩阵数学方面】+【大一阶段的编程科目如Pascal, C, C++, Java】。

语言要求:

雅思总分:7

雅思听力:6.5

雅思阅读:6.5

雅思阅读:6.5

雅思口语:6.5

雅思写作:6.5

托福总分:100

托福听力:23

托福写作:25

托福口语:23

托福阅读:23

世界排名 数据来源: QS世界排名

51

QS排名

专业课程

Required modules:所需模块 Individual Project credits: 个人项目学分 Scientific Computing for Finance credits: 金融学分的科学计算 Quantitative Methods in Finance credits: 金融学分的定量方法 Case Studies in Finance credits: 金融学分的案例研究 Agent Based Modelling in Finance credits: 金融学分中的基于代理的建模 High Frequency Finance credits: 高频金融学分 Optional modules: 可选模块 Financial Markets credits: 金融市场学分 Fundamentals of Digital Signal Processing credits: 数字信号处理学分基础 Cryptography credits: 密码学学分 C for Financial Mathematics credits: C金融数学学分 Nature Inspired Learning Algorithms credits: 自然启发学习算法学分 Statistics in Finance credits: 金融学分统计 Software Engineering Underlying Technology for Financial Systems credits: 金融系统软件工程基础技术学分 Distributed Ledgers Crypto currencies credits: 分布式分类账加密货币学分 Security Management credits: 安全管理学分 Machine Learning credits: 机器学习学分

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