R programming Training from experienced professionals
R Programming Training In Nagpur is designed by a team of professionals to offer hands-on experience instead of only theoretical notions. Students will gain industry exposure as well as credibility through an end of course project work based on real-life use case

R programming Training in Nagpur, with Real-time Practice and Live Projects

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R Programming Training in Nagpur course overview

R Programming Training in Nagpur R is a completely free, open-source programming language and software environment for graphics and statistical computing. It is a widely popular statistic and Data Management programming language used by millions of organizations all over the world in order to manage their large amount of data accurately and comfortably R Programming Training in Nagpur R has gradually become one of the most popular languages used by a colossal number of Data Science Professionals everywhere throughout the world. It is additionally exceptionally noticeable on the checklist of the Gartner Magic Quadrant of Advanced Analytics. Trends and surveys delineate that R is used by almost 70% of data miners and is developing at a development rate quicker than some other data science language. R Programming has an easy-to-use syntax and interface that makes it most loved of each software engineer, data investigator, analyst, and marketers. Learn R programming and gain knowledge on the best way to Extract, Analyze, and Present Data. Further, Data science course with R programming and insights will make your vocation solid in Statistical Computing, Data Analytics, Business Reporting, and Intelligence.
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Prerequisites of R Programming Training in Nagpur

It is not necessary to have knowledge of any programming language before you start this Python course but you must have some practical experience of any other programming language. just you aware about Prior scripting experience or knowledge of fundamental programming concepts is the must.  
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Training from professional R Programer

Appzmine developer has been implementing professional Analaytic solutions across a range of organization for many years. Those consultants write and teach our R Programming training in Nagpur courses, so their experience directly informs course content.
R Programming Training in Nagpur Course Content
Introduction to R
  • R language for statistical programming
  • The various features of R
  • Introduction to R Studio
  • The statistical packages
  • Familiarity with different data types and functions
  • Learning to deploy them in various scenarios
  • Use SQL to apply ‘join’ function
  • Components of R Studio-like code editor
  • Visualization and debugging tools
  • Learn about R-bind.
R-Packages
  • R Functions
  • Code compilation and data in the well-defined format called R-Packages
  • Learn about the R-Package structure
  • Package metadata and testing
  • CRAN (Comprehensive R Archive Network)
  • Vector creation and variables values assignment.
Sorting Dataframe
  • R functionality
  • Rep Function
  • Generating Repeats
  • Sorting and generating Factor Levels
  • Transpose and Stack Function
Matrices and Vectors
  • Introduction to matrix and vector in R
  • Understanding the various functions like merge
  • Strsplit, Matrix manipulation
  • RowSums
  • RowMeans
  • ColMeans
  • Collums
  • Sequencing, repetition
  • Indexing and other functions.
Reading data from external files
  • Understanding subscripts in plots in R
  • How to obtain parts of vectors
  • Using subscripts with arrays
  • As logical variables, with lists
  • Understanding how to read data from external files.
Generating plots
  • Generate plot in R
  • Graphs, Bar Plots
  • Line Plots, Histogram
  • Components of Pie Chart.
Analysis of Variance (ANOVA)
  • Understanding Analysis of Variance (ANOVA) statistical technique,
  • Working with Pie Charts
  • Histograms
  • Deploying ANOVA with R
  • One way ANOVA
  • Two way ANOVA.
K-means Clustering
  • K-Means Clustering for Cluster & Affinity Analysis
  • Cluster Algorithm
  • A cohesive subset of items
  • Solving clustering issues
  • Working with large datasets
  • Association rule mining affinity analysis for data mining and analysis and learning co-occurrence relationships.
Association Rule Mining
  • Introduction to Association Rule Mining
  • The various concepts of Association Rule Mining
  • Various methods to predict relations between variables in large datasets
  • The algorithm and rules of Association Rule Mining, understanding single cardinality.
Regression in R
  • Understanding what is Simple Linear Regression
  • The various equations of Line, Slope
  • Y-Intercept Regression Line
  • Deploying analysis using Regression
  • The least square criterion
  • Interpreting the results
  • Standard error to estimate and measure of variation.
Analysing Relationship with Regression
  • Scatter Plots
  • Two variable Relationship
  • Simple Linear Regression analysis
  • A line of best fit
Advance Regression
  • Deep understanding of the measure of variation
  • The concept of co-efficient of determination
  • F-Test, the test statistic with an F-distribution
  • Advanced regression in R
  • Prediction linear regression.
Logistic Regression
  • Logistic Regression Mean
  • Logistic Regression in R.
Advance Logistic Regression
  • Advanced logistic regression
  • Understanding how to do prediction using logistic regression
  • Ensuring the model is accurate
  • Understanding sensitivity and specificity
  • Confusion matrix, what is ROC
  • A graphical plot illustrating binary classifier system
  • ROC curve in R for determining sensitivity/specificity trade-offs for a binary classifier.
Receiver Operating Characteristic (ROC)
  • Detailed understanding of ROC
  • The area under ROC Curve
  • Converting the variable
  • Dataset partitioning
  • Understanding how to check for multicollinearity
  • How two or more variables are highly correlated?
  • Building of model
  • Advanced dataset partitioning
  • Interpreting the output
  • Predicting the output
  • Detailed confusion matrix
  • Deploying the Hosmer-Lemeshow test for checking whether the observed event rates match the expected event rates.
Kolmogorov Smirnov Chart
  • Data analysis with R
  • Understanding the WALD test
  • MC Fadden’s pseudo R-squared
  • The significance of the area under ROC Curve
  • Kolmogorov Smirnov Chart which is non-parametric test of one dimensional probability distribution.
Database connectivity with R
  • Connecting to various databases from the R environment
  • Deploying the ODBC tables for reading the data
  • Visualization of the performance of the algorithm using Confusion Matrix.
Integrating R with Hadoop
  • Creating an integrated environment for deploying R on Hadoop platform,
  • Working with R Hadoop
  • RMR package and R Hadoop Integrated Programming Environment
  • R programming for MapReduce jobs and Hadoop execution.

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Why Chooce Us

  • Training from professional R Programming developers
  • 10 years of experience
  • Training and Internship combined
  • Real-Time Development experience
  • Fully Equipped Lab, With AC & WIFI Internet available
  • Support and Careers Advice
  • We Offer Quality Training
  • and so much more…

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