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Start Date between Jan 24 - July 25

Programming for Data Science icon

If you began your programme between January 2024 and July 2025, you will always find your modules in this section.

Start Date between Jan 24 - July 25

Exploratory Data Analysis image

OMAT5102M Exploratory Data Analysis

£1250.00

Description

This course will introduce students to basic techniques, which can be used to perform a preliminary investigation of data sets. Exploring data involves visualising the variables and relationships to help determine outliers, identify trends, suggest suitable statistical models and inform future data gathering.
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Exploratory Data Analysis image

OMAT5102M Exploratory Data Analysis (Alumni)

£1125.00

Description

This course will introduce students to basic techniques, which can be used to perform a preliminary investigation of data sets. Exploring data involves visualising the variables and relationships to help determine outliers, identify trends, suggest suitable statistical models and inform future data gathering.
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Data Science image

OMAT5204M Data Science

£1250.00

Description

Data scientists work in a wide range of fields of application. This module gives an insight into some general principles of the work of a data scientist and some of the underpinnings of artificial intelligence and statistics in the practice of data science.
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Data Science image

OMAT5204M Data Science (Alumni)

£1125.00

Description

Data scientists work in a wide range of fields of application. This module gives an insight into some general principles of the work of a data scientist and some of the underpinnings of artificial intelligence and statistics in the practice of data science.
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Multivariate Methods image

OMAT5205M Multivariate Methods

£1250.00

Description

In big data with multiple variables, it is vital to discover pattern and infer valuable information from the data. This module introduces basic techniques from multivariate statistics, with the aim to discover, describe and exploit dependencies between variables in complex datasets.
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Multivariate Methods image

OMAT5205M Multivariate Methods (Alumni)

£1125.00

Description

In big data with multiple variables, it is vital to discover pattern and infer valuable information from the data. This module introduces basic techniques from multivariate statistics, with the aim to discover, describe and exploit dependencies between variables in complex datasets.
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Statistical computing image

OMAT5300M Statistical Computing

£1250.00

Description

The use of computers in mathematics and statistics provides a wide range of techniques for studying otherwise intractable problems and for analysing very large data sets. "Statistical computing" is the branch of mathematics which concerns these techniques for situations which either directly involve randomness, or where randomness is used as part of a mathematical model. This module gives an overview of key methods in statistical computing. One of the most important ideas in statistical computing is, that often properties of a stochastic model can be found experimentally, by using a computer to generate many random instances of the model, and then statistically analysing the resulting sample. The resulting methods are called Monte Carlo methods, and discussion of such methods forms the main focus of this module.
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Statistical computing image

OMAT5300M Statistical Computing (Alumni)

£1125.00

Description

The use of computers in mathematics and statistics provides a wide range of techniques for studying otherwise intractable problems and for analysing very large data sets. "Statistical computing" is the branch of mathematics which concerns these techniques for situations which either directly involve randomness, or where randomness is used as part of a mathematical model. This module gives an overview of key methods in statistical computing. One of the most important ideas in statistical computing is, that often properties of a stochastic model can be found experimentally, by using a computer to generate many random instances of the model, and then statistically analysing the resulting sample. The resulting methods are called Monte Carlo methods, and discussion of such methods forms the main focus of this module.
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