R Programming course

With the help of this course, you'll learn how to utilize R effectively for data analysis. Software for statistical programming environments must be installed, and a high-level language implements the most common programming language ideas. R programming, reading data into R, using R packages, developing R functions, debugging, profiling R code, and structuring and commenting on R code is covered in the course. Working examples will be drawn from statistical data analysis topics.
Several programs include this course as a requirement.

Several different Specializations and Professional Certificate programs will accept this credit. The knowledge you get from completing R Programming course will transfer to the following programs:

  • R Foundations in Data Science Specialization
  • Expertise in the field of data science
  • R Programming training from an industry expert

    Data manipulation using K Programming complex analytics concepts such as data mining and regression using RStudio, data visualization, and more will be taught by industry specialists in the Programming online Certification Course. Their R Programming certification training online helps students to take R Programming certification into diverse industries, allowing them to analyze data and make efficient business decisions.

    After completing the R Programming course, students will receive a certificate proving they've completed the program. All major corporations throughout the world acknowledge this certificate as legitimate. Learners who get a certification in R Programming are more likely to land high-paying employment.

    R Programming course with machine learning

    There are many advantages to using the R programming language to implement machine learning.

    • It has a lot of helpful documentation. You can use R for machine learning projects at an early stage because it gives the right statistical strategy for working with data with fewer lines of code.
    • R is ideal for visualizing data. R is a programming language that allows for building models that can be used in machine learning. R supports machine learning model development.
    • The R language provides the best tools and library packages available for machine learning projects. Developers can create pre-model, model, and post-model using these packages. R is the go-to language for machine learning tasks due to its more comprehensive and robust packages than Python's.

    Popular Machine Learning R Language Packages

    The lattice software can create graphs illustrating the variable or relation between many variables with conditions.R package Data Explorer aims to automate the viewing and handling of data so the user may focus on the project's findings.

    This package, known as Dalex (Descriptive Machine Learning Explanations), helps explain the relationship between the variables that are considered input and those that are considered output. It aids in the comprehension of sophisticated machine learning models.Machine learning tabular data can be summarized with dplyr, an R package. A "split, apply and combine" strategy is used.Data exploration is facilitated by the Esquisse R package, which is used for this purpose. This tool can also plot bar graphs, histograms, and scatterplots.Predictive models may be built more quickly with a caret, an R program that does just that.

    This R package contains functions for cleaning up soiled data. It's designed for beginners and intermediates. Classification and regression models can be built utilizing two-stage techniques with the help of the R package, rpart. The models are represented using binary trees as their data structure.

    How R is used in machine learning

    Numerous high-profile organizations, such as Google, Facebook, and Uber, use R for Machine Learning. The following are the applications:

    • To look for patterns and trends
    • Gaining knowledge about user behavior
    • To discover the connections among the users
    • Finding and implementing logical solutions
    • Using charting components to gain access
    • Adding interactive visual visuals to your content


    The emphasis of this course will be on practical applications of the primary method that enables us to design and implement prediction functions. After completing this course, students will be able to do the following tasks with confidence:

    • Comprehend the algorithmic components
    • Use various machine learning techniques to develop and assess predictive models using real-world data.
    • Learn how to use different classification algorithms to filter Email data
    • Time series forecasting
    • With the use of a case study, perform clustering.

    In addition to video lectures and hands-on exercises, R Programming course includes additional assignments for self-study in the final section and working files with the first lesson.

    Who should take this course:

    Analytics specialists who will use Machine Learning techniques to examine big data, Data scientists who will detect, analyze and explain trends or patterns in complicated data sets, Experts in both software and analytics

    R Programming course Near me

    R is an open-source statistical computing and graphics programming language and environment. R is a valuable tool for managing data and storage facilities in organizations. It offers a set of operators for working with arrays in particular matrices. R Programming course Near me is the best choice.

    Please fill enquiry form to get curriculm, more details please contact +91-9945339324

    No, you do not require any experience to start this program. But we expect that you should know basic usages of compute system.
    Statisticians and data miners use R extensively for data analysis and statistical software development in data science.
    While Python has become the industry standard for many data scientists and statisticians, R is still frequently utilized for numerous reasons.
    R is a challenging programming language for beginners to learn, but experienced developers should have no problem.
    By the end of this course, you will have learned how to utilize the R programming language to create statistical applications. These skills will help you win jobs as data analysts.
    • How to work with the R programming language and its associated environment.
    • How to modify data with R functions
    • How to use R for data analysis and manipulation

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