R programming Online Training

The programming course will teach you how to manipulate data using R, visualise data, and use RStudio for advanced analytics topics such as regressions and data mining.You will be trained on real-world projects and assignments to grasp Data Science abilities during this Programming course.

R Programming Course Description

Needintech provides comprehensive Data Science with R certification training for professionals looking to broaden their knowledge base and launch a career in this industry. You will grasp many parts of tools and concepts used in R programming, such as graphical representation, statistical analysis, and reporting, with this industry-designed R course. This online R programming course will also teach you the principles of functions, data structures, variables, and flow of control. After completing the R programming training successfully, you will be given the Intellipaat R Certification.

Mock Interviews

Needintech's mock interviews provide a platform for you to prepare for, practise for, and experience a real-life job interview. You will have an advantage over your colleagues if you familiarise yourself with the interview environment beforehand in a comfortable and stress-free environment.

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Course Objetives
  •  We don’t expect you to have any prior expertise for this certification course. fundamental understanding of programming languages, on the other hand, can be beneficial in learning programming abilities.
  • Data Analysts and Software Engineers
  • Professionals in Business Intelligence
  • SAS Developers interested in learning open-source technologies
  •  Those interested in a career in Data Science and Data Analytics
  • You should enrol in our programming course because:
  • According to an IBM study, 70% of businesses believe analytics is critical to decision making.
  • The Analytics market is growing at pace of 19% per year, according to Pringle Company.
  • programmers can make more than $110,000 per year  O’Reilly Poll
  • programming is statistical language for Data Science specialisation that is gaining popularity due to its extensibility.
  • It is simply scalable and can be widely implemented for variety of applications. Taking this Data Science with certification training to study numerous techniques in programming would thus enable you to land high-paying positions with huge corporations.
  • This course’s tools and technologies are as follows: well-known package for creating visuals.
  • dplyr: popular package for quickly manipulating data.
  • tidyr: An package for cleaning up data sets.
  • readr: An package for reading in data.
  • Understand the fundamentals of ‘R’.
  • Learn how to make zero-value transition from existing computer software to ‘R-based’ system.
  • Gain thorough understanding of analytics as well as proficiency in approaches and systems.
  • Learn about data science as career option using real-world data.
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Syllabus of R Programming Online Course

  • Understanding Business Analytics and R
  • Compare R with other software in analytics
  • Install R
  • Perform basic operations in R using command line
  • Learn the use of IDE R Studio
  • Use the ‘R help’ feature in R


Module 2: Introduction to R programming


      • This module starts from the basics of R programming like datatypes and functions.
      • In this module, we present a scenario and let you think about the options to resolve it, such as which datatype should one to store the variable or which R function that can help you in this scenario.
      • You will also learn how to apply the ‘join’ function in SQL.


      • Variables in R
      • Scalars
      • Vectors
      • Matrices
      • List
      • Data frames
      • Using c, Cbind, Rbind, attach and detach functions in R
      • Factors

Module 3: Data Manipulation in R


      • In this module, we start with a sample of a dirty data set and perform Data Cleaning on it, resulting in a data set, which is ready for any analysis.
      • Thus using and exploring the popular functions required to clean data in R.


      • Data sorting
      • Find and remove duplicates record
      • Cleaning data
      • Recoding data
      • Merging data
      • Slicing of Data
      • Merging Data
      • Apply functions

Module 4: Data Import techniques in R


      • This module tells you about the versatility and robustness of R which can take-up data in a variety of formats, be it from a csv file to the data scraped from a website.
      • This module teaches you various data importing techniques in R.


      • Reading Data
      • Writing Data
      • Basic SQL queries in R
      • Web Scraping

Module 5: Exploratory Data Analysis


        • In this module, you will learn that exploratory data analysis is an important step in the analysis.
        • EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis. You will also learn about the various tasks involved in a typical EDA process.


        • Box plot
        • Histogram
        • Pareto charts
        • Pie graph
        • Line chart
        • Scatterplot
        • Developing graphs

Module 6: Overview of Machine Learning techniques


        • This module touches the base Statistics, Machine learning techniques used in the Industry and will cover case studies.


        • Standard deviation
        • Outlier
        • Linear regression
        • Multiple regression
        • Logistic regressions
        • Correlation

Module 7: Project Work

      • 1 Real-time project

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