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Practical Engineering Data Mining: Techniques and Uses

This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive...

By Kirankumar Trivedi on Coursera

About This Course

This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive review of the essential fundamentals and central concepts underpinning data mining. Additionally, it introduces pivotal data mining methodologies and offers a guide to executing these techniques through various algorithms. Students will be introduced to a range of data mining techniques, such as data preprocessing, the extraction of association rules, classification, prediction, clustering, and the exploration of complex data, and will implement a capstone project exploring the same. Additionally, we will use case studies to explore the application of data mining across diverse sectors, including but not limited to manufacturing, healthcare, medicine, business, and various service industries.

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Frequently Asked Questions

How much does Practical Engineering Data Mining: Techniques and Uses cost?

Visit the Practical Engineering Data Mining: Techniques and Uses course page for current pricing and available discounts.

Who teaches Practical Engineering Data Mining: Techniques and Uses?

Practical Engineering Data Mining: Techniques and Uses is taught by Kirankumar Trivedi, Northeastern University .

What skill level is Practical Engineering Data Mining: Techniques and Uses for?

This course is designed for beginner learners.

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Students0
Duration4 hours
LevelBeginner
Languageen
PlatformCoursera