Learn to use the "Data Mining with R" (DMwR) package and R software to build and evaluate predictive data mining models.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Understand how to implement and evaluate a variety of predictive data mining models in three different domains, each described as extended case studies: (1) harmful plant growth; (2) fraudulent transaction detection; and (3) stock market index changes.
Perform sophisticated data mining analyses using the "Data Mining with R" (DMwR) package and R software.
Have a greatly expanded understanding of the use of R software as a comprehensive data mining tool and platform.
Understand how to implement and evaluate supervised, semi-supervised, and unsupervised learning algorithms.
This comprehensive Case Studies in Data Mining with R curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
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What you need before starting this Case Studies in Data Mining with R course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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