项目简介

Your theoretical learning will be at a high mathematical level, while the technical and practical skills you will gain will enable you to apply advanced methods of data science and statistics to investigate real world questions.

通过本项目的学习，你的理论学习将达到很高的数学水平，而获得的技术和实践技能将使你有能力应用先进的数据科学和统计学方法来调查现实世界的问题。

The compulsory courses on the MSc Data Science programme will provide you with comprehensive coverage of some fundamental aspects of data, computational techniques and statistical analysis. You will then choose courses from a range of options ranging from Distributed Computing for Big Data and Statistical Computing, to Financial Statistics and Probabilistic Methods in Risk Management and Insurance. The programme will combine traditional lectures with computer lab sessions, in which you will work with data to complete hands-on exercises using programming tools.

数据科学项目课程的必修课程全面覆盖数据、计算技术和统计分析的基本方面。你将选择一系列课程，从分布式计算大数据和统计计算，金融统计和风险管理和保险的概率方法。本课程将结合传统的讲座和计算机实验室课程，其中你将使用编程工具与数据来完成实际练习。

The MSc Data Science Capstone Project will provide you with a unique opportunity to apply knowledge gained from the programme by working on a real-world data science project in cooperation with a company. The Capstone Project company partners in the academic year 2017/18 included Facebook, Google, Microsoft, Microsoft Research, Virgin Atlantic, SpecSavers, Proximity London and Tesco. The Capstone Projects have covered a wide range of data science problems involving analysis of various types of data such as social media data, customer behaviour data, and company network data.

MSc数据科学毕业项目将为您提供一个独特的机会，通过在一个真实的数据科学项目与一家公司合作工作，来应用从该项目中获得的知识。2017/18学年的毕业项目合作伙伴公司包括Facebook、Google、Microsoft、Microsoft Research、Virgin Atlantic、SpecSavers、Pro.ityLondon和Tesco。毕业项目涵盖了广泛的数据科学问题，包括分析各种类型的数据，如社会媒体数据、客户行为数据和公司网络数据。

项目基本信息

Start date

项目申请开始日期

30 September 2019

2019/9/30

Application deadline

截止日期

None – rolling admissions. However please note the funding deadlines

无截止日期，报满为止

Duration

学习时长

12 months full-time only

全日制12个月

Applications 2017

17年申请人数

372Intake 2017

实际录取人数

20AvailabilityUK/EU: Open from October

Overseas: Open from October

海外学生8月可开始申请

Tuition fee

学费

UK/EU: £28,056

Overseas £28,608

海外学生28608英镑

Financial supportGraduate support scheme (deadline 26 April 2019), ESRC funding as part of a four year award (deadline 7 January 2019)Minimum entry requirement

最低录取标准

2:1 degree or equivalent in a relevant discipline, including a substantial amount of mathematics

获得相关学科的二等一学士学位，包括数学相关的学科，或其他同等资格证书

GRE/GMAT requirementNone

不需要GMAT,GRE成绩

英语要求

雅思：综合得分7.0,单项R6.5 L6.5 W6.0 S6.0

托福：综合得分100，单项R23 L22 W22 S20

Location Houghton Street, London

项目结构

必修课

Computer Programming

计算机编程

Managing and Visualising Data

管理和视觉化数据

Data Analysis and Statistical Methods*

数据分析和统计方法

Machine Learning and Data Mining

机器学习和数据挖掘

Capstone Project

毕业项目

选修课

论文1

MY470 Computer Programming (0.5)

OR

Students who can demonstrate equivalent prior knowledge of MY470, via trans of prior qualifications, may instead take a further 0.5 unit course from Paper 5:

Paper 5 options list

论文2

ST445 Managing and Visualising Data (0.5)

论文3

ST447 Data Analysis and Statistical Methods (0.5) #

OR

Students who can demonstrate equivalent prior knowledge of ST447, via trans of prior qualifications, may instead take a further 0.5 unit course from Paper 5:

Paper 5 options list

论文4

ST443 Machine Learning and Data Mining (0.5) #

论文5

Courses to the value of 1.0 unit(s), including at least 0.5 unit(s) of ST courses from the following:

MA407 Algorithms and Computation (0.5) #

MA424 Modelling in Operations Research (0.5) #

MY459 Special Topics in Quantitative Analysis: Quantitative Text Analysis (0.5) #

MY461 Social Network Analysis (0.5)

ST449 Artificial Intelligence and Deep Learning (0.5)

ST451 Bayesian Machine Learning (0.5) #

ST405 Multivariate Methods (0.5) #

ST411 Generalised Linear Modelling and Survival Analysis (0.5) #

ST422 Time Series (0.5) #

ST429 Statistical Methods for Risk Management (0.5) #

ST436 Financial Statistics (0.5) #

ST444 Statistical Computing (0.5)

ST446 Distributed Computing for Big Data (0.5) #

论文6

ST498 Capstone Project (1.0)

就业方向

Data scientists are much in demand across industry, including a variety of Internet online service companies, marketers, banks, investment management, and other financial companies.

数据科学家在整个行业中需求量很大，需求行业包括互联网在线服务公司、营销人员、银行、投资管理以及其他金融公司。

Data scientist positions involve a wide range of responsibilities; such as conducting exploratory data analysis, applying statistical methodologies, deriving business insights from data, partnering with company executives, product and engineering teams to solve problems, identify trends and opportunities, inform, influence, support, and execute product decisions and launches.

数据科学家的职位职责广泛，如进行探索性的数据分析，应用统计方法，从数据中得出商业见解，与公司高管、产品和工程团队合作，解决问题，识别趋势和机会NIT、通知、影响、支持和执行产品决策和发布。

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