R Programming Training

R Programming Training

Course Description

R is the most widely used tool for statistical programming. It is powerful, versatile and easy to use. It is the first choice for thousands of data analysts working in both companies and academia. This course will help you master the basics of R in a short time, as a first step to become a skilled R data scientist. The course is meant for absolute beginners, so you don’t have to know anything about R before starting. (You don’t even have to have the R program on your computer) But after graduating this course you will have the most important R programming skills – and you will be able to further develop these skills, by practicing, starting from what you will have learned in the course. We here at Codec Networks will ensure that you are not left behind in this fast moving world of Big Data and its Use in sense of Analytics.

R programming Training Certification language and its packages implement a wide variety of statistical and graphical techniques, including linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering that is becoming more and more popular for doing data science. Companies worldwide are using R programming language to harvest insights from their data and get a competitive edge. Unlike any other R programming language tutorial, this course focuses on R language specifically for data science. In our Intro to R language class, you will learn about powerful ways to store and manipulate data as well as cool data science tools to start your own analyses. Enroll with Codec Networks course to get started with R programming Certification Training.

Who Should Attend

This course is intended for learners who have basic R or programming background, and want to apply statistics, machine learning, information visualization, data analysis, and text analysis techniques to gain new insight into data. The class is taught in a tutorial format using the multiple packages, and only a minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.

Modules Covered

  • Introduction to Programming with R.
  • Getting to know R Studio and Anaconda Navigator.
  • Vectors
  • Data Analysis Process
  • Metrices
  • Factors
  • List
  • DataFrames
  • Basic Graphics in R
  • Data Transformation with dplyr
  • Workflow Scripts
  • Exploratory Data Analysis
  • Data Import with readr
  • ModelBasic with modelr
  • Data Visualization
  • R Markdown
  • Graphics for communication with ggplot2
  • Visualization Case Study
  • Project

Course Duration

  • Fast Track: : 5 Days (8 Hours/Day)
  • Regular Track: : 4 Weeks (2 Hours/Day)
  • Weekend Track : 6 Weekends (3 Hours/Day)

Post Training Program (CODEC Networks Specialty)

  • Live Project Work
  • Extensive Classroom Training
  • Internship Opportunity with experts and R & D team

Package Includes

  • Weekly Assignments, Reference codes & Study material in PDF format
  • Module-wise Case Studies/ Projects
  • Career Guidance & Career Support
  • The completion of some selected assignments & case studies
  • Training certificate from CODEC Networks

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