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Course Title: Data Mining and Big Data
Dr Ali Emrouznejad
Pre-requisites:
Basic knowledge of calculus and statistics, quantitative skills would be an advantage
Course description:
Applications of data mining are highly useful in today's competitive market with big data. Data
mining is the process of ‘mining’ large quantity of data to extract useful information. It involves
searching through databases for potentially useful information such as knowledge rules,
patterns, regularities, and other trends hidden in the data.
An understanding of business analytics and data mining concepts and techniques can offer a
valuable advantage in the competition for jobs and placements. This sector remains one of just
a few areas showing consistent growth in terms of job opportunities and salaries even during
recession.
The aim of this course is to introduce many of the important idea in data mining with focus
of analysing big data, explain them as statistical framework, and describe some of their
applications in Business, Finance, Marketing, and Management. Hence, this course covers data
mining techniques and their use in managerial business decision making.
In this course several case studies of well-known data mining methods are used; e.g. shopping
basket analysis such as Tesco club card, credit card / insurance fraud detection, predicting
stock market returns, risk analysis in banking.
Course outlines
[1] Discuss data mining from an analytical perspective and demonstrate its application to
business decision making;
[2] Combine practical experience with the theoretical insight needed to reveal patterns and
valuable information hidden in big data sets, and their applications to real-world problems;
[3] Develop analytical and computer modelling skills necessary to analyse big data;
[4] Demonstrate the ability to use data mining packages such as IBM-Modeler in order to carry
out a data mining project.