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UPCOMING BATCHE(S) IN "PUNE" (change city)

Date Time Course Type Price Option

Module 1:-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.

Module 2:-R-Packages

•          R Functions

•          Code compilation and data in well-defined format called R-Packages

•          Learn about R-Package structure

•          Package metadata and testing

•          CRAN (Comprehensive R Archive Network)

•          Vector creation and variables values assignment

Module 3:-Sorting Data frame

•          R functionality

•          Rep Function

•          Generating Repeats

•          Sorting and generating Factor Levels

•          Transpose and Stack Function

Module 4:-Matrices and Vectors

•          Introduction to matrix and vector in R

•          understanding the various functions like Merge

•          Strsplit

•          Matrix manipulation

•          rowSums, rowMeans, colMeans, colSums, sequencing, repetition, indexing and other functions

Module 5:-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

Module 6:-Generating plots

•          Generate plot in R, Graphs, Bar Plots, Line Plots, Histogram, components of Pie Chart.

Module 7:-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

Module 8:-K-means Clustering

•          K-Means Clustering for Cluster & Affinity Analysis

•          Cluster Algorithm

•          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.

Module 9:-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

Module 10:-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

Module 11:-Analyzing Relationship with Regression

•          Scatter Plots,

•          Two variable Relationship

•          Simple Linear Regression analysis

•          Line of best fit

Module 12:-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

Module 13:-Logistic Regression

•          Logistic Regression Mean

•          Logistic Regression in R.

Module 14:-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

•          Graphical plot illustrating binary classifier system

•          ROC curve in R for determining sensitivity/specificity trade-offs for a binary classifier.

Module 15:-Receiver Operating Characteristic (ROC)

•          Detailed understanding of ROC

•          Area under ROC Curve, converting the variable,

•          Data set partitioning

•          Understanding how to check for multi co linearity

•          How two or more variables are highly correlated

•          Building of model

•          Advanced data set partitioning

•          Interpreting of 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.

Module 16:-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.

Module 17:-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

Module 18:-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

  • Learn to Install RStudio and work on R interface
  • Learn the basics of R programming including objects, classes, vectors, attributes etc.
  • Write functions including generic functions using various methods and loops
  • Install various packages and work effectively in the R environment
  • Select and modify values as required
  • Learn to use Vectorized Coding and Use Cases
  • Cover the concepts of R Notation, S3 System and Closures
  • Become proficient in writing a fundamental program and perform analytics with R

·         Certified Trainer & Consultants rich industry experience

·         Practical Approach & Not just the slides

·         Mind Mapping, Group Exercise, Role Play & Flash Cards

·         Ample Course ware and practice questions

·         Live  Projects Exposure

·         Hands on Experience of Salesforce Development

·         1 Month Classroom workshop with Exclusive courseware

·         100% Preparation with Hands on Experience & Mock Exam Sessions

·         Excellent Pre & Post Professional Training Support 

·         Very Affordable Pricing with high Quality Training 

·          Online Access to each participant

·         Industry Specific Assignments mandatory for each participant

·         100 % Placement Assistance

·         Knowledge built up as per Industry Standards



Yes, We provide 100% Job Assistance to all IEVISION students. 
A dedicated HR – Recruitment members are designated to assist you in preparing your professional resume building, guiding you on HR Interview Process, Sending your resumes to corporates and assist you till you get placed.
Since last 6 years, IEVISION Students are placed in many countries and most of the MNC companies in India.

After course completion, Participation Certificate will be awarded.  We do also support in getting the Global Certification, Please connect with our support staff and you will be assisted.

We are operating from central location in Pune. Visit Contact us  
IEVISION Representative will be happy to assist you. +919604642000 & +919604647000 or email us at

Yes, we do provide demonstration sessions for all Technology Courses. Demo lectures are delivered by real trainers who have years of Industry Experience. You can clear all your doubts about the training course, courseware, training approach, live projects, job placement, fees, installments and over all association.
IEVISION Trainers are working professionals, highly experienced, certified on various levels on particular technologies with hands-on industry experience. Trainers are motivated to build the strong technical capability of students to achieve their objectives in life.
Yes, IEVISION provide 100% Practical Oriented training and students will be working on minimum 2 live projects.
Batch size is kept limited for effective delivery of training program. Based on training program, 5 - 15 students are adjusted in a batch.
We do provide batch change option. Please contact our support staff for more information about upcoming batches.
Yes, IEVISION provide the latest courseware in the form on Hardcopy, PDF and PPTs. 
IEVISION facility is fully equipped with required Hardware & Software. You are allowed to use your laptop & required software shall be assisted.

If you miss any session, you can attend classes in any other running batch or next upcoming batch. Please contact our Counsellor for more information about running batches

Yes, 5% discount is provided for Lump sum payment.

Yes, IEVISION provide installment facility based.
IEVISION accept payment through various mode Online Trasfer, Cheque, Cash, Credit Card, Debit Card and Demand Draft.