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Courses>Data Science>Data Mining with Rattle
DevelopmentData Mining with Rattle
Price:Paid
Length:15 hours
Content type:video
level:all levels
Updated:05 March 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Data Science>Data Mining with Rattle
Data Mining with Rattle
3.9 (1.6k)
15 hours
1615 students
What you will learn
1Perform and support life-cycle data mining tasks and activities using the popular Data Miner ("Rattle") software suite.
2Understand the functionalities implicit in the data, explore, test, transform, cluster, associate, model, evaluate, and log tabs in the Data Miner ("Rattle") GUI software platform.
3Know how to explore, visualize, transform, and summarize data sets in Rattle.
4Know how to create advanced, interactive Ggobi visualizations of data.
5Know how to use, estimate and interpret: cluster analyses; association analyses mining rules; decision trees; random forests; boosting; and support vector machines using Rattle.
Target audiences
1Anyone interested in data mining seeking to master the use of a powerful popular contemporary (and no-cost) Data Mining software suite
2Data analytics professionals seeking to augment their data mining skill sets with a popular and useful data mining package.
3Undergraduate and graduate students seeking to attain in-demand data mining skills for data analysis/mining tasks to offer to prospective employers.
Requirements
1Students will need to install the R console and RStudio software (instructions are provided).
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

Data Mining with Rattle is a unique course that instructs with respect to both the concepts of data mining, as well as to the "hands-on" use of a popular, contemporary data mining software tool, "Data Miner," also known as the 'Rattle' package in R software. Rattle is a popular GUI-based software tool which 'fits on top of' R software. The course focuses on life-cycle issues, processes, and tasks related to supporting a 'cradle-to-grave' data mining project. These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms. It is both a conceptual and a practical course as it teaches and instructs about data mining, and provides ample demonstrations of conducting data mining tasks using the Rattle R package. The course is ideal for undergraduate students seeking to master additional 'in-demand' analytical job skills to offer a prospective employer. The course is also suitable for graduate students seeking to learn a variety of techniques useful to analyze research data. Finally, the course is useful for practicing quantitative analysis professionals who seek to acquire and master a wider set of useful job skills and knowledge. The course topics are scheduled in 10 distinct topics, each of which should be the focus of study for a course participant in a separate week per section topic.

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Careertail
Courses>Data Science>Data Mining with Rattle
DevelopmentData Mining with Rattle
Price:Paid
Length:15 hours
Content type:video
level:all levels
Updated:05 March 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Data Science>Data Mining with Rattle
Data Mining with Rattle
3.9 (1.6k)
15 hours
1615 students
What you will learn
1Perform and support life-cycle data mining tasks and activities using the popular Data Miner ("Rattle") software suite.
2Understand the functionalities implicit in the data, explore, test, transform, cluster, associate, model, evaluate, and log tabs in the Data Miner ("Rattle") GUI software platform.
3Know how to explore, visualize, transform, and summarize data sets in Rattle.
4Know how to create advanced, interactive Ggobi visualizations of data.
5Know how to use, estimate and interpret: cluster analyses; association analyses mining rules; decision trees; random forests; boosting; and support vector machines using Rattle.
Target audiences
1Anyone interested in data mining seeking to master the use of a powerful popular contemporary (and no-cost) Data Mining software suite
2Data analytics professionals seeking to augment their data mining skill sets with a popular and useful data mining package.
3Undergraduate and graduate students seeking to attain in-demand data mining skills for data analysis/mining tasks to offer to prospective employers.
Requirements
1Students will need to install the R console and RStudio software (instructions are provided).
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

Data Mining with Rattle is a unique course that instructs with respect to both the concepts of data mining, as well as to the "hands-on" use of a popular, contemporary data mining software tool, "Data Miner," also known as the 'Rattle' package in R software. Rattle is a popular GUI-based software tool which 'fits on top of' R software. The course focuses on life-cycle issues, processes, and tasks related to supporting a 'cradle-to-grave' data mining project. These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms. It is both a conceptual and a practical course as it teaches and instructs about data mining, and provides ample demonstrations of conducting data mining tasks using the Rattle R package. The course is ideal for undergraduate students seeking to master additional 'in-demand' analytical job skills to offer a prospective employer. The course is also suitable for graduate students seeking to learn a variety of techniques useful to analyze research data. Finally, the course is useful for practicing quantitative analysis professionals who seek to acquire and master a wider set of useful job skills and knowledge. The course topics are scheduled in 10 distinct topics, each of which should be the focus of study for a course participant in a separate week per section topic.

Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot