項目簡介

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.

通過本項目的學習，你的理論學習將達到很高的數學水平，而獲得的技術和實踐技能將使你有能力應用先進的數據科學和統計學方法來調查現實世界的問題。

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.

數據科學項目課程的必修課程全面覆蓋數據、計算技術和統計分析的基本方面。你將選擇一系列課程，從分佈式計算大數據和統計計算，金融統計和風險管理和保險的概率方法。本課程將結合傳統的講座和計算機實驗室課程，其中你將使用編程工具與數據來完成實際練習。

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數據科學畢業項目將爲您提供一個獨特的機會，通過在一個真實的數據科學項目與一家公司合作工作，來應用從該項目中獲得的知識。2017/18學年的畢業項目合作伙伴公司包括Facebook、Google、Microsoft、Microsoft Research、Virgin Atlantic、SpecSavers、Pro.ityLondon和Tesco。畢業項目涵蓋了廣泛的數據科學問題，包括分析各種類型的數據，如社會媒體數據、客戶行爲數據和公司網絡數據。

項目基本信息

Start date

項目申請開始日期

30 September 2019

2019/9/30

Application deadline

截止日期

None – rolling admissions. However please note the funding deadlines

無截止日期，報滿爲止

Duration

學習時長

12 months full-time only

全日制12個月

Applications 2017

17年申請人數

372Intake 2017

實際錄取人數

20AvailabilityUK/EU: Open from October

Overseas: Open from October

海外學生8月可開始申請

Tuition fee

學費

UK/EU: £28,056

Overseas £28,608

海外學生28608英鎊

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

最低錄取標準

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

獲得相關學科的二等一學士學位，包括數學相關的學科，或其他同等資格證書

GRE/GMAT requirementNone

不需要GMAT,GRE成績

英語要求

雅思：綜合得分7.0,單項R6.5 L6.5 W6.0 S6.0

託福：綜合得分100，單項R23 L22 W22 S20

Location Houghton Street, London

項目結構

必修課

Computer Programming

計算機編程

Managing and Visualising Data

管理和視覺化數據

Data Analysis and Statistical Methods*

數據分析和統計方法

Machine Learning and Data Mining

機器學習和數據挖掘

Capstone Project

畢業項目

選修課

論文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

論文2

ST445 Managing and Visualising Data (0.5)

論文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

論文4

ST443 Machine Learning and Data Mining (0.5) #

論文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) #

論文6

ST498 Capstone Project (1.0)

就業方向

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

數據科學家在整個行業中需求量很大，需求行業包括互聯網在線服務公司、營銷人員、銀行、投資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.

數據科學家的職位職責廣泛，如進行探索性的數據分析，應用統計方法，從數據中得出商業見解，與公司高管、產品和工程團隊合作，解決問題，識別趨勢和機會NIT、通知、影響、支持和執行產品決策和發佈。

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