R Data Mining Projects

This fast-paced video tutorial will help you solve predictive modeling problems using the most popular data mining algorithms through simple, practical cases. Practical and focused on real-world data mining cases, this course covers concepts such as spatial data mining, text mining, social media mining, and web mining.

  • 3 hours 19 minutes of Self Paced Video
  • Make use of statistics and programming to understand data mining concepts and their application
  • Use R programming to apply statistical models to data
  • Get to know various data visualization libraries available in R to represent data
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Self-Paced

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Course Features

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About R Data Mining Projects

The R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis. It enables you to create high-level graphics and offers an interface to other languages. This means R is best suited to producing data and visual analytics through customization scripts and commands, instead of the typical statistical tools that provide tick boxes and drop-down menus for users.

This video course explores data mining techniques, showing you how to apply different mining concepts to various statistical and data applications in a wide range of fields. We will teach you about R and its application to data mining, and give you relevant and useful information you can use to develop and improve your applications. It will help you complete complex data mining cases and guide you through handling issues you might encounter during projects.

Course Objectives
  • Make use of statistics and programming to understand data mining concepts and their application
  • Use R programming to apply statistical models to data
  • Use various libraries available in R CRAN (comprehensive R archives network) in data mining
  • Apply data management steps to handle large datasets
  • Get to know various data visualization libraries available in R to represent data
Curriculum
Module 1:

Data Manipulation Using In-Built R Data

Module 2:

Exploratory Data Analysis With Automobile Data

Module 3:

Visualizing Diamond Dataset

Module 4:

Regression With Automobile Data

Module 5:

Market Basket Analysis With Groceries Data

Instructor

Self Paced courses are comprised of several learning videos into a course structure broken down into Learning Modules and Sessions. The learner is required to go through the videos topic-wise in the structure sequence of the course to learn the concepts. Being Self Paced, there is no intervention of any external faculty or additional mentor in learning.

Certification

NIIT Certification on completion of the program.

Pre-requisites

Basic knowledge of data analysitcs and basic programming background with Math or Statistics background.

FAQs

Who should go for this Course?

This course comes as an ideal choice for Data Science professionals involved in complex data analytics and data mining techniques. Professionals working on Data Mining Projects can also pursue this course to help them gain an extra edge over sophisticated data mining algorithms development using R Language.

Course Features

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