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⚡ Overview

In Introduction to R, you will master the basics of this widely used open source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.

Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science. Every year, the number of R users grows by about 40%, and an increasing number of organizations are using it in their day-to-day activities. Begin your journey to learn R with us today!

Program starts with basics of R Programming, evolving into How to work with Data in R; Importing the Data, Preparing the Data, Analysing the Data in R and Visualization of the results in R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

Learn the most popular tool for data analytics

Start with the R basics, to advance Programming in R

Hybrid Learning with Guided practice & Weekly Practice quiz questions on the app along with the classroom sessions

Extensive Learning hours with 44 hours of classroom training including the classroom assessment with additional 42 hours of online guided practice for better learning and increased retention

Future of R Programming Language

R is the most popular language used by Data Scientists & Statisticians. It is estimated that there are approximately 2 million users of R. Thousands of people around the world are contributing to R with Data Science Course technology along with their team. It is considered to be as the game-changer because R programming has turned out to be the best data analytical tool.

Some More

About R Programming

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

  • An effective data handling and storage facility,
  • A suite of operators for calculations on arrays, in particular matrices,
  • A large, coherent, integrated collection of intermediate tools for data analysis,
  • Graphical facilities for data analysis and display either on-screen or on hardcopy, and
  • A well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
  • The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.

    R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.

    BRILLIANCE has been awarded as “Best IT and Education Training Company”. It delivers high-quality R Programming training. This course has been especially designed to prepare students for a job in the analytics space. This training is delivered on the short duration as well as long term basis. Any technical student or corporate person can join this training.

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R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

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    The company has designed training programs for both students and professionals separately. R Programming course with BRILLIANCE provides an extensive coverage of a number of advanced R Programming concepts and their implementation in real-time projects. The training offers hands-on experience with a number of common R Programming concepts.

    With world-class infrastructure and a dynamic team of experienced faculty, BRILLIANCE provides the R Programming training in Jaipur. After completion of the R Programming program at BRILLIANCE, the students are awarded a global Certificate which is recognized as well as accepted not only in India but also in foreign countries. The training process at BRILLIANCE comprises of both classroom as well as practical sessions which will make students capable of handling complex and difficult situation when they would join the corporate world.

    Training in R programming is available on weekdays as well as weekends. Special Classes can also be scheduled as per requirement. Its industry-focused curriculum is in line with the international standards to make sure that the training prepares our students for jobs not just in India but foreign countries too. Apart from that, it makes all its efforts to provide placement in top MNC’s to its certified students.

    Other benefits of training BRILLIANCE-

    • Hands-on Mode of Teaching as well as opportunity to work on live projects.
    • 100% Placement Support for all Students.
    • Proficient and Skilled Trainers from the Industry.
    • Flexible Batch Timings.
    • Small Batch Size for individual attention.
    • 1-year Membership Card.
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There are certain proven steps to follow in order to effectively command of the R Programming.Some of them are:

  • Warming up.
  • Setting up your machine.
  • Learn the basics of R language.
  • Understanding the R community.
  • Importing and manipulating your data.
  • Effective Data Visualization.
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Target Audience in R Programming course

Graduates who want to build career in this field.

They Can Do.

Professionals working in data science and analytics industry.

They Can Do.

Professionals looking for a career switch into data science and analytics.

They can Do.

FAQs

  • What machines does R run on?
    • R is being developed for the Unix-like, Windows and Mac families of operating systems. Support for Mac OS Classic ended with R 1.7.1..

  • Why is R named R?
    • The name is partly based on the (first) names of the first two R authors (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell Labs language ‘S’

  • How can I create an R package?
    • A package consists of a subdirectory containing a file DESCRIPTION and the subdirectories R, data, demo, exec, inst, man, po, src, and tests (some of which can be missing). The package subdirectory may also contain files INDEX, NAMESPACE, configure, cleanup, LICENSE, LICENCE, COPYING and NEWS. See section “Creating R packages” in Writing R Extensions, for details. This manual is included in the R distribution, and gives information on package structure, the configure and cleanup mechanisms, and on automated package checking and building. R version 1.3.0 has added the function package.skeleton() which will set up directories, save data and code, and create skeleton help files for a set of R functions and datasets.

  • How can I set components of a list to NULL?
    • You can use

      x[i] <- list(NULL)

      to set component i of the list x to NULL, similarly for named components. Do not set x[i] or x[[i]] to NULL, because this will remove the corresponding component from the list. For dropping the row names of a matrix x, it may be easier to use rownames(x) <- NULL, similarly for column names.

  • How does autoloading work?
    • R has a special environment called .AutoloadEnv. Using autoload(name, pkg), where name and pkg are strings giving the names of an object and the package containing it, stores some information in this environment. When R tries to evaluate name, it loads the corresponding package pkg and reevaluates name in the new package’s environment. Using this mechanism makes R behave as if the package was loaded, but does not occupy memory (yet). See the help page for autoload() for a very nice example.

Course Duration

3 Months

Timings

2 Hours

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STUDENTS FEEDBACK

Pariskhit Goyal

Just completed my training from Brilliance in R programming and i am very impress for the teaching way and they are using latest technology totally very satisfied. A big thanks to my trainer.

3 months

Rohan Sharma

I have done my training in R programming from brilliance it techno. its a really very good experience for me. The experts are very knowledgeable and they helped me alot every time now I am placed in a very good company due to training provided by brilliance.

8 months

Shivani Gupta

I am Shivani Gupta. I have learnt a lot of new things in r programming from brilliance. Best trainer and teaching us a lot more than the syllabus and he focusses more on practical knowledge which is very important for our future placement perspective. Best coaching center for R Programming

4 months

Armaan Malik

I completed my R Training from Brilliance. They have a team of proficient trainers who teaches even the difficult concepts in very easy manner. It is a good place for learning. Overall nice experience.

2 months

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