8251 modules
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COMP6237 2029-30
Data Mining
The challenge of data mining is to transform raw data into useful information and actionable knowledge. Data mining is the computational process of discovering patterns in data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and data management.
This course will introduce key concepts in data mining, information extraction and information indexing; including specific algorithms and techniques for feature extraction, clustering, outlier detection, topic modelling and prediction of complex unstructured data sets. By taking this course you will be given a broad view of the general issues surrounding unstructured and semi-structured data and the application of algorithms to such data. At a practical level you will have the chance to explore an assortment of data mining techniques which you will apply to problems involving real-world data. -
STAT6144 2026-27
Data Mining
New sources of data in a wide range of formats contain valuable information, but extracting this information is often challenging using traditional tools. This module introduces modern techniques for analysing such data and demonstrates how they may be put into action. Methods for handling structured and unstructured data are discussed, including techniques for the analysis of textual data. -
MATH6183 2026-27
Data Mining and Analytics
The module provides an introduction to data analytics and data mining. It will combine practical work using R and SQL with an introduction to some of the theory behind standard data mining techniques. -
MATH6183 2027-28
Data Mining and Analytics
The module provides an introduction to data analytics and data mining. It will combine practical work using R and SQL with an introduction to some of the theory behind standard data mining techniques. -
MATH6183 2028-29
Data Mining and Analytics
The module provides an introduction to data analytics and data mining. It will combine practical work using R and SQL with an introduction to some of the theory behind standard data mining techniques. -
MATH6183 2025-26
Data Mining and Analytics
The module provides an introduction to data analytics and data mining. It will combine practical work using R and SQL with an introduction to some of the theory behind standard data mining techniques. -
MANG3056 2028-29
Data Mining for Marketing
Companies nowadays have collected a large volume of data from various sources. This module aims to introduce the key concepts of using ‘Big Data’ to improve marketing activities. Specifically, it focuses of the use of data mining techniques to manage customer relationships. Relevant marketing issues such as customer surveys, profiling/segmentation, communications, campaign measurement, satisfaction, loyalty, profitability, social media and other current topics will be discussed with regard to how data mining and analytical approaches can be used to improve marketing decision making. In this module, students will get hands-on experience and will be introduced to software commonly used in marketing departments and organisations. Thus, this module seeks to equip students with key skills needed to manage real marketing decisions based on marketing data. -
MANG3056 2027-28
Data Mining for Marketing
Companies nowadays have collected a large volume of data from various sources. This module aims to introduce the key concepts of using ‘Big Data’ to improve marketing activities. Specifically, it focuses of the use of data mining techniques to manage customer relationships. Relevant marketing issues such as customer surveys, profiling/segmentation, communications, campaign measurement, satisfaction, loyalty, profitability, social media and other current topics will be discussed with regard to how data mining and analytical approaches can be used to improve marketing decision making. In this module, students will get hands-on experience and will be introduced to software commonly used in marketing departments and organisations. Thus, this module seeks to equip students with key skills needed to manage real marketing decisions based on marketing data. -
SESA1018 2026-27
Data Science & Computational Methods
“The purpose of computing is insight, not numbers” (Hamming, 1962). Data science is all about gaining insight from the large amounts of data we are surrounded by.
In our digital world, engineers need to be able to use a range of tools, technologies and platforms to make sense of data and tackle complex engineering problems.
In this module you will
- Become confident in using a whole range of data science techniques
- Enhance your digital skills
- Learn about how, where and when to use a range of important computational tools, technologies and platforms
This module will help become proficient in the digital skills you need for everyday and engineering tasks throughout your degree and beyond. -
SESA1018 2025-26
Data Science & Computational Methods
“The purpose of computing is insight, not numbers” (Hamming, 1962). Data science is all about gaining insight from the large amounts of data we are surrounded by.
In our digital world, engineers need to be able to use a range of tools, technologies and platforms to make sense of data and tackle complex engineering problems.
In this module you will
- Become confident in using a whole range of data science techniques
- Enhance your digital skills
- Learn about how, where and when to use a range of important computational tools, technologies and platforms
This module will help become proficient in the digital skills you need for everyday and engineering tasks throughout your degree and beyond.