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Discover the versatility of R for data mining with this collection of real-world dataset analysis techniques

R Data Mining Projects

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Discover the versatility of R for data mining with this collection of real-world dataset analysis techniques

  • Video Duration:04 Hours
  • Cost: $ 124.99

Course Details

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.

Who all can attend

This course is ideal for data analysts from novice to intermediate level.. You should have prior knowledge of basic statistics and a little bit of programming language experience in any tool or platform.

What you will learn from this course

  • 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

Course Content

  1. Data Manipulation Using In-Built R Data
    • The Course Overview
    • What Is Data Mining?
    • Introduction to the R Programming Language
    • Data Type Conversion
    • Sorting, Merging, Indexing, and Subsetting Dataframes
    • Date and Time Formatting
    • Types of Functions
    • Loop Concepts
    • Applying Concepts
    • String Manipulation
    • NA and Missing Value Management and Imputation Techniques

  2. Exploratory Data Analysis with Automobile Data
    • Univariate Data Analysis
    • Bivariate Analysis
    • Multivariate Analysis
    • Understanding Distributions and Transformation
    • Interpreting Distributions and Variable Binning
    • Contingency Tables, Bivariate Statistics, and Checking for Data Normality
    • Hypothesis Testing
    • Non-Parametric Methods

  3. Visualizing Diamond Dataset
    • Introduction to Data Visualization
    • Visualizing Charts, and Geo Mapping
    • Visualizing Scatterplot, Word Cloud and More
    • Using plotly
    • Creating Geo Mapping

  4. Regression with Automobile Data
    • Introduction about Regression
    • Linear Regression
    • Stepwise Regression Method for Variable Selection
    • Logistic Regression
    • Cubic Regression

  5. Market Basket Analysis with Groceries Data
    • Introduction to Market Basket Analysis
    • Practical project

Contact Us

Instructor-led online training is also available for the same course.

For more details, write to us at :

Call(+91) 8130666206/209

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