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Understand key principles of R programming. Join today to learn from an R programming expert.

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Course Duration

32 Hrs.

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2 Project

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  • Croma Campus is a leading R programming training institute that offers the best R programming training to students looking to get a secured job in an MNC and corporate giant.
    • R users grow by about 40%, and organizations are using it in their day-to-day activities.

      Hiring companies include Google, Bing, Facebook, Uber, Twitter, and Ford.

      Being used for purposes like cleaning the data, forecasting, creating mind-blowing visualizations.

      R is a highly demanded data analytics skill among all.

      Get hands-on R programming training and become a certified professional.

  • Our R Programming Training at Croma Campus is mainly aimed at becoming an expert in the R language. So, what are you waiting for Simply enrol for the best R Programming certification course and get a secured job without investing much.

R Programming Training

About-Us-Course

  • No matter whether you are a professional or a novice, our R Programming training course may help you learn all the skills required and let you implement them at work.
    • Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

      Learn to use R to clean, analyse, and visualize data.

      Learn how to use GitHub to manage data science projects.

      Perform regression analysis, least squares and inference using regression models.

      Learn the most popular tool for data analytics.

  • So, what are you waiting for simply enrol for the best R Programming training course and learn all the skills to outperform others at the time of interview.

  • R programming is one of the fastest-growing languages and has undergone a successful span of more than 25 years as far as its adoption is concerned. This success also reveals a promising future scope of r programming language.
    • Glassdoor has ranked Data Science with a median base salary of $110000 and 4,524 job openings.

      It is the fastest-growing tech employment area today.

      Job profiles include Data Scientist, Analytics Manager, Database Administrator, Data Engineer, etc.

      Your salary will increase as you gain knowledge and experience.

  • Upon the completion of your R Programming training course, your career will grow like wildfire. With attractive salary packages and designation, your career will skyrocket and get ahead by standing tall above the rest.
    • You will get a better knowledge of programming and how to implement it.

      Enhanced knowledge of the web development framework to develop dynamic websites swiftly.

      Increased chances of working in leading software companies like Infosys, Wipro, Amazon, TCS, IBM and many more.

      Learn how to design, develop, test, support and deploy desktop, custom web, and mobile applications.

      Design and improve testing and maintenance activities and procedures.

  • R ultimately established to be an inexpensive, Custom-Made, and inflatable statistical analysis solution. R has lots of packages/libraries that contain numerous helpful functions that you can employ for your use. R is considered as an abundance who are all getting into the analytics field.
    • Nearly 40% started a new career after completing this specialization.

      Nearly 20% got a pay increase or promotion.

      R has become the preferred computing environment for the statistical community.

      The number of R users enlarges by 40%

  • After the completion of your course, you will need to perform a multitude of job roles and responsibilities at work. Here are a few of them;
    • Development, automate and review technical architecture, requirements and statistical models.

      Coordinate with end users for designing and implementation of analytics solutions as per the needs of the project.

      Participate in team problem-solving efforts and offer ideas to solve client issues.

      Design of experiments/data collection for statistical analysis.

      Program code of qualitative variable and manipulation tasks with various statistical methodologies

      Continually look for ways to improve the overall performance of systems.

  • Our R Programming training course is suggested for all those novices and specialists who are keen on working in the analytics industry. R is now well thought out to be not just the most popular open-source analytic tool but the most popular analytics tool in the world.
    • There is always an adequate job opportunity for R programming.

      Some of the top hiring industries in R programming include Infosys, Spectra, IBM, TCS, QA Infotech, and more.

      R is suitable for all IT professionals like Big Data analytics, Business analytics, scientific research

      There is also insufficiency in analytics for professionals with R programming skills.

  • When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
    • Our certification is accredited worldwide.

      Increases the value of your resume and you can attain leading job posts.

      Get noticed by the potential recruiters, and get hired right away.

      Our experts also support you by providing interview tips.

Why Should You Learn R Programming?

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Plenary for R Programming Training

Track Week Days Weekends Fast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
Training Mode Classroom/Online Classroom/Online Classroom/Online
Course Price at :
19,80022,000
10% OFF Expires in01D 08H 53M 23S

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100%

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BATCH TIMINGS

R Programming Training Upcoming Batches

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25-Mar-2024*

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CURRICULUM & PROJECTS

R Programming Training

  • This course is suggested for all those novices and specialists who are keen on working in the analytics industry. R is suitable for all IT professionals like Big data analytics, Business analytics, scientific research, statistical reporting, Econometrics, social science, business intelligence, and business development. Researchers who perform data analysis with higher dimensional graphs. Students who need R for their courses. Prerequisite It is not necessary to have any prior knowledge of R. R is now well thought out to be not just the most popular open-source analytic tool but the most popular analytics tool in the world
  • In this program you will learn:
    • Overview :

      R Programming Basics.

      Variable types and data structures in base R.

      Getting data into the R environment.

      Data frame manipulation.

      Handling dates in R.

      Exploratory Data Analysis (Descriptive Statistics).

      Working with text data.

      Control flow & functions.

      Graphics in R Overview.

      Advanced R graphics.

      Inferential Statistics.

      General Linear Regression Models in R.

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  • Overview:
    • History of R

      Advantages and disadvantages

      Downloading and installing

      How to find documentation

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  • R Programming Basics:
    • Using the R console and R Studio

      Getting help

      Learning about the environment

      Writing and executing scripts

      Object oriented programming

      Introduction to vectorised calculations

      Introduction to data frames

      Installing and loading packages

      Working directory

      Saving your work

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  • Variable types and data structures in base R:
    • Variables and assignment

      Data types

      Numeric, character, Boolean, and factors

      Data structures

      Vectors, matrices, arrays, data frames, lists

      Indexing, sub-setting

      Assigning new values

      Viewing data and summaries

      Naming conventions

      Objects

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  • Getting data into the R environment:
    • Built-in data

      Reading data from structured text files

      Reading data using ODBC

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  • Data frame manipulation:
    • Introduction to tables, enhanced data frames

      Renaming columns

      Adding new columns

      Binning data (continuous to categorical)

      Combining categorical values

      Transforming variables

      Handling missing data

      Merging datasets together

      Stacking datasets together (concatenation)

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  • Handling dates in R:
    • Date and date-time classes in R

      Formatting dates for modeling

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  • Exploratory Data Analysis (Descriptive Statistics):
    • Continuous data

      Distributions

      Quantiles, mean

      Bi-modal distributions

      Histograms, box-plots

      Categorical data

      Tables

      Bar plots

      Group by calculations

      Split-apply-combine

      Reshaping and pivoting data in R (long to wide with aggregation)

      Melt and cast

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  • Working with text data:
    • Finding and matching patterns in text

      Stringer package for text manipulation

      Introduction to regular expressions in R

      Categorical data wrangling with forcats

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  • Control flow & functions:
    • Truth testing

      Branching

      Looping

      Functions

      Parameters

      Return values

      Variable scope

      Exception handling

      Applying functions across dimensions

      Sapply, lapply, apply

      Programming with map and purr

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  • Graphics in R Overview:
    • Base graphics system in R

      Scatterplots, histograms, bar charts, box and whiskers, dot plots

      Labels, legends, titles, axes

      Exporting graphics to different formats

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  • Advanced R graphics:
    • Understanding the grammar of graphics

      Quick plots (qplot function)

      Building graphics by pieces (ggplot function)

      Understanding geoms (geometries)

      Linking chart elements to variable values

      Controlling legends and axes

      Exporting graphics

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  • Inferential Statistics:
    • Bivariate correlation

      T-test and non-parametric equivalents

      Chi-squared test

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  • General Linear Regression Models in R:
    • Understanding formulas

      Linear and logistic regression models

      Regression plots

      Confounding / interaction in regression

      Evaluating residuals

      Scoring new data from models (prediction)

      Useful plots from regression models

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  • Placement Guide:
    • Tips to clear an Interview

      Common Interview questions and answers

      R programming Interview Questions and Answers

      Resume Building Guide

      Attempt for the related Global Certification Exam

      Earn Credentials and Start applying for Jobs

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+ More Lessons

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Mock Interviews

Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.
How Croma Campus Mock Interview Works?

Projects

Validate your skills and knowledge by working on industry-based projects that includes significant real-time use cases.Gain hands-on expertize in Top IT skills and become industry-ready after completing our project works and assessments.Our projects are perfectly aligned with the modules given in the curriculum and they are picked up based on latest industry standards. Add some meaningful project works in your resume, get noticed by top industries and start earning huge salary lumps right away.
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FAQ's

The R Programming Courses at Croma Campus shall be opted by any freshers who want to learn the language.

The R Programming Training does not ask for any requisites.

We accept all major kinds of payment options such as Net Banking, Cash, Card, etc.

You will receive globally recognized course completion certification from Croma Campus.

Yes, we provide interview tips that will help you to ace the examination.

Career Assistancecareer assistance
  • - Build an Impressive Resume
  • - Get Tips from Trainer to Clear Interviews
  • - Attend Mock-Up Interviews with Experts
  • - Get Interviews & Get Hired
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