Fundamentals of Data Mining
Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. The field of data mining has evolved from the disciplines of statistics and artificial intelligence.

This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective.

45 mins (self-paced)   |   841 students enrolled
You will not be billed to complete this course. This course has 3 modules.
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Knowledge and skills that will be awarded by this course.
Why should I take this course?

Data mining is a powerful tool used to discover patterns and relationships in data. You will learn how data mining principles are applied to the dissection of large complex data sets, including those in very large databases or through web mining. Explore, analyze and leverage data and turn it into valuable, actionable information for yourself or your company.

What resources will I need for this course?

An internet enabled device and a PushCV account.

What is the most useful thing I'll learn if I take this course?

At the end of this course you will have a fundamental knowledge of how statistical methods are used to extract meaning from large datasets, how predictive models and analytics are developed and used, and you will understand and use strategic decision-making techniques in data exploration.

Curriculum (Course Modules)

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