授课型硕士 · 2027

数据科学理学硕士

Data Science MSc

理学硕士MSc

学制

全日制 12 个月Full-time: 12 months

授课

全日制Full-time

学费

英镑 34,800 · UK fees: £14,600; International fees: £34,800GBP 34,800 · UK fees: £14,600; International fees: £34,800

英语

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入学要求

2:1 (or international equivalent) with an affinity for programming and/or advanced statistics evidenced through prior study or practical experience detailed in the application. Graduates from other fields, with strong mathematics and/or computer science background will be considered with 60% average mark.

学年课程

核心模块全部学生Core module for all students

binary search trees (red-black trees)
动态编程dynamic programming
graph-algorithms (eg shortest path, maximum flows)
amortized analysis
priority queues (binary, leftist and Fibonacci heaps)
string algorithms (string matching, longest common subsequence)
public-key cryptography (the RSA cryptosystem)
the page-rank algorithm (from Google search)
neural networks
基础统计学basic statistics
types of data
数据可视化技术data visualisation techniques
数据建模data modelling
data pre-processing methods including data imputation
forecasting methods
clustering and classification methods
the nature of uncertainty captured by fuzzy sets and associated links to human reasoning
inference using fuzzy sets
similarity of fuzzy sets
design and modelling of information via fuzzy sets
type-1 fuzzy sets
type-2 fuzzy sets
fuzzy logic systems
fuzzy set based applications
运营研究仿真operations research simulation
社会仿真social simulation
数据科学data science
automated scheduling
决策分析decision analysis
机器学习基础machine learning foundations
pattern recognition foundations
artificial neural networks
深学习deep learning
应用机器学习applications of machine learning
数据采矿技术data mining techniques
evaluating hypotheses
the growing amounts of data
the relational database management systems (RDBMS)
an overview of Structured Query Languages (SQL)
an introduction to NoSQL databases
the difference between a relational DBMS and a NoSQL database
how to identify the need to employ a NoSQL database
task environments
reactive, deliberative and hybrid architectures for individual agents
architectures and coordination mechanisms for multi-agent systems

必修Students with a degree in Computer Science or equivalent are required to obtain between 40 and 80 credits from the following list of Computer Science modules

binary search trees (red-black trees)
动态编程dynamic programming
graph-algorithms (eg shortest path, maximum flows)
amortized analysis
priority queues (binary, leftist and Fibonacci heaps)
string algorithms (string matching, longest common subsequence)
public-key cryptography (the RSA cryptosystem)
the page-rank algorithm (from Google search)
neural networks
基础统计学basic statistics
types of data
数据可视化技术data visualisation techniques
数据建模data modelling
data pre-processing methods including data imputation
forecasting methods
clustering and classification methods
the nature of uncertainty captured by fuzzy sets and associated links to human reasoning
inference using fuzzy sets
similarity of fuzzy sets
design and modelling of information via fuzzy sets
type-1 fuzzy sets
type-2 fuzzy sets
fuzzy logic systems
fuzzy set based applications
运营研究仿真operations research simulation
社会仿真social simulation
数据科学data science
automated scheduling
决策分析decision analysis
机器学习基础machine learning foundations
pattern recognition foundations
artificial neural networks
深学习deep learning
应用机器学习applications of machine learning
数据采矿技术data mining techniques
evaluating hypotheses
the growing amounts of data
the relational database management systems (RDBMS)
an overview of Structured Query Languages (SQL)
an introduction to NoSQL databases
the difference between a relational DBMS and a NoSQL database
how to identify the need to employ a NoSQL database
task environments
reactive, deliberative and hybrid architectures for individual agents
architectures and coordination mechanisms for multi-agent systems

必修And are then required to obtain between 20 and 60 credits from the remaining list of Computer Science modules

基础统计学basic statistics
types of data
数据可视化技术data visualisation techniques
数据建模data modelling
data pre-processing methods including data imputation
forecasting methods
clustering and classification methods
机器学习基础machine learning foundations
pattern recognition foundations
artificial neural networks
深学习deep learning
应用机器学习applications of machine learning
数据采矿技术data mining techniques
evaluating hypotheses
运营研究仿真operations research simulation
社会仿真social simulation
数据科学data science
automated scheduling
决策分析decision analysis
the nature of uncertainty captured by fuzzy sets and associated links to human reasoning
inference using fuzzy sets
similarity of fuzzy sets
design and modelling of information via fuzzy sets
type-1 fuzzy sets
type-2 fuzzy sets
fuzzy logic systems
fuzzy set based applications
the growing amounts of data
the relational database management systems (RDBMS)
an overview of Structured Query Languages (SQL)
an introduction to NoSQL databases
the difference between a relational DBMS and a NoSQL database
how to identify the need to employ a NoSQL database
task environments
reactive, deliberative and hybrid architectures for individual agents
architectures and coordination mechanisms for multi-agent systems

Mathematical Sciences modules

common univariate probability distributions
joint and conditional distributions
parameter estimation (for example via maximum likelihood)
confidence intervals
hypothesis testing
统计建模statistical modelling

必修Students without a degree in Mathematical Sciences or equivalent are required to obtain 20 to 60 credits from the following list of Mathematical Science modules

common univariate probability distributions
joint and conditional distributions
parameter estimation (for example via maximum likelihood)
confidence intervals
hypothesis testing
统计建模statistical modelling

申请节点

September 2027

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