R-Programming Training

R-Programming Training Course

Palium Skills offers multiple R-Programming related courses. Each course has different levels each more advanced than the other.

The certification and course details are as follows -

R-Programming courses are available at 3 levels - Fundamentals - 24 hours, Advanced - 24 hours and Business Data Analysis using R-Programming

Click on the buttons inside the tabbed menu:

Course Description

This course from Palium Skills offers R-Programming training for individuals and corporates. Such courses are offered during weekdays and weekends.
 
What skills will the student gain?
After the completion of this course, the student will be able to:

  • Learn the basics of R-Programming.
  • ·   Learn the use of online tools like Facebook, Instagram and others in Social Media Advertising.
  • ·   Be able to start working in the R-Programming domain
  • ·   Learn the nuances of r-Programming and how it can be used for advanced applications.
  • ·   Be able to do basic application design using r-Programming
  • ·   Prepare and get ready to work in this domain

Mode of Training

The classes are delivered during Weekday or Weekend in classroom or online modes

Locations:

The training is offered in locations like Chennai, Bangalore, Kolkata, Mumbai and NCR.

To know more about the schedules in those cities click here -->

Schedule for Kolkata

Outside the country it is delivered in Dhaka, Thimpu, Singapore, Kuala Lumpur, Middle East, Africa and Australia.

Detailed Course Contents for R-Programming Course:

Introduction

  • Getting R and Getting Started
  • Getting and Using R
  • A First R Session
  • Moving around in R
  • Working with Data in R
  • Dealing with Missing Data in R

Programming in R :

  • What is Programming?
  • Getting Ready to Program
  • The Requirements for Learning to Program
  • Flow Control
  • Essentials of R Programming
  • Understanding the R Environment
  • Implementation of Program Flow in R
  • A First R Program
  • Example - finding Pythagorean Triples
  • Using R to Solve Quadratic Equations
  • Why R is Object-Oriented

Writing Reusable Functions:

  • Examining R Function from Base-R Code
  • Creating a Function
  • Calculating a Confidence Interval for a

Mean:

  • Avoiding Loops with Vectorized Operations
  • Vectorizing If-Else Statement Using ifelse()
  • Making More Powerful Functions
  • Any, All, and Which
  • Making Functions More Useful
  • Confidence Intervals Revisited

Summary Statistics:

  • Measuring Central Tendency
  • Measuring Location via Standard Scores
  • Measuring Variability
  • Covariance and Correlation
  • Measuring Symmetry (or Lack Thereof)

Creating Tables and Graphs:

  • Frequency Distributions and Tables
  • Pie Charts and Bar Charts
  • Boxplots
  • Histograms
  • Line Graphs
  • Scatterplots
  • Saving and Using Graphics

Discrete Probability Distributions:

  • Discrete Probability Distributions
  • Bernoulli Processes
  • Relating Discrete Probability to Normal Probability

Creating Confidence Intervals:

  • Confidence Intervals for Means
  • Confidence Intervals for Proportions
  • Understanding the Chi-Square Distribution
  • Confidence Intervals for Variances and Standard Deviations
  • Confidence Intervals for Differences between Means
  • Confidence Intervals Using the stats Package

Performing t Tests:

  • A Brief Introduction to Hypothesis Testing
  • Understanding the t Distribution
  • The One-Sample t Test
  • The Paired-Samples t Test
  • Two-Sample t Tests
  • A Note on Effect Size for the t Test

One-Way Analysis of Variance:

  • Understanding the F Distribution
  • Using the F Distribution to Test Variances
  • Compounding Alpha, Post Hoc Comparisons
  • One-Way ANOVA
  • Using the anova Function

Advanced Analysis of Variance:

  • Two-Way ANOVA
  • Repeated-Measures ANOVA
  • Mixed-Factorial ANOVA

Correlation and Regression:

  • Covariance and Correlation
  • Regression
  • An Example: Predicting the Price of Gasoline
  • Determining Confidence and Prediction Intervals

Multiple Regression:

  • The Multiple Regression Equation
  • Multiple Regression Example: Predicting Job Satisfaction
  • Using Matrix Algebra to Solve a Regression Equation
  • Brief Introduction to the General Linear Model
  • More on Multiple Regression

Logistic Regression:

  • What is Logistic Regression?
  • Logistic Regression with One Dichotomous

Predictor:

  • Logistic Regression with One Continuous
  • Logistic Regression with Multiple Predictors
  • Comparing Logistic & Multiple Regression
  • Alternatives to Logistic Regression

Chi-Square Tests:

  • Chi-Square Tests of Goodness of Fit
  • Chi-Square Tests of Independence
  • A Special Case: Two-by-Two Contingency

Tables:

  • Relating the Standard Normal Distribution to Chi-Square
  • Effect Size for Chi-Square Tests
  • Demonstrating the Relationship of Phi to the Correlation Coefficient

Nonparametric Tests:

  • Nonparametric Alternatives to t Tests
  • Nonparametric Alternatives to ANOVA
  • Nonparametric Alternatives to Correlation

Using R for Simulation:

  • Defining Statistical Simulation
  • Some Simulations in R

The "New" Statistics—Resampling and Bootstrapping:

  • The Pitfalls of Hypothesis Testing
  • The Bootstrap
  • Jackknifing
  • Permutation Tests
  • More on Modern Robust StatisticalMethods

Making an R Package:

  • The Concept of a Package
  • Some Windows Considerations
  • Establishing the Skeleton of an R Package
  • Editing the R Documentation
  • Building and Checking the Package
  • Installing the Package
  • Making Sure the Package Works Correctly
  • Maintaining Your R Package

The R Commander Package:

  • The R Commander Interface
  • Examples of Using R Commander for Data Analysis

Schedule

If you are located outside Kolkata or would like to attend our session during your visit to Kolkata then please feel free to write us at palium.skills@gmail.com for any queries related to program,
upcoming schedule and fee. Call: +91-9051092035 or WhatsApp: +91-9051092035

Schedule for Advanced Excel Training in 2018 is as follows:
Month Dates No of Hours
January Completed
February Completed
March Completed
April Completed
May Completed
June Completed
July Completed
August Completed 16
September 23rd, 30th, 7th, 14th 16
October TBA 16
November 4th - fast-track,6th - weekday 16
December 2nd - fast-track, 4th - weekday 16

Study Mode & Fees

Course Name Delivery Mode Fees
R-Programming Fundamentals Classroom Rs. 7,000 + 18% GST
R-Programming Advanced Classroom Rs. 8,000 + 18% GST
R-Programming Fundamentals Online Rs. 7,000 + 18% GST
R-Programming Advanced Online Rs. 8,000 + 18% GST

FAQs

The commonly asked questions pertaining to R-Programming training are -

Q: What are the pre-requisites for taking this course?

A: Good Understanding of Statistics and basic understanding of Programming algorithm

Q: Will this be theoretical or hands-on?

A: This is a complete hands-on workshop where the trainer will demonstrate and participants will learn the rich and diverse experience in this domain.

Q: Will you help me to get projects to work on?

A: Yes, we can help you to get projects on which you can work from home.

Q: Will you help me to create a application for my project?

A: Yes, we can help you create a application for your project. Separate charges may apply.

Q: What if I have doubts after completing the class?

A: You can gather your doubts and come by prior appointment to get your doubts cleared.

Q: Will there be an exam at the end of the course?

A: No, an evaluation exam is not conducted at the end of the course.

Q: Will I receive a certificate for the course?

A: Yes, participants receive a certificate after completing the course provided they have attended 90% of the class.

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