Embrace the power of data analytics and visualization with our comprehensive training program—Certified R Developer. The R programming language, known for its open-source nature and advanced analytics capabilities, is now a driving force in the world of predictive analytics and data visualization. Enroll in this transformative program to become a Certified R Developer and position yourself at the forefront of the rapidly growing demand for R proficiency.

Unlock the Power of R: Understand the basics of the R programming language and explore its vast capabilities for predictive analytics and data visualization. Gain proficiency in manipulating, analyzing, and visualizing data using the powerful features of R.
Hands-On Learning: Experience a problem-solving-based approach to learning, with hands-on assignments and quizzes that reinforce your knowledge. Benefit from relevant examples and case studies that make the learning process effective and enjoyable.
Comprehensive Curriculum: Dive deep into the world of R with a curriculum that covers data types, structures, statistical tests, data visualization techniques, data manipulation, flow control, debugging tools, and statistical modeling—including simple and multiple regression, logistic regression, clustering, and PCA.

Training Duration: 3 Days

SBL-Khas Claimable
Certificate Of Completion Available
Private In-House Class Available
ILT & VILT Class Available

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CRD: Certified R Developer

RM3,300.00

The R programming language is an open source scripting language for predictive analytics and data visualization. R is growing into one of the most popular and in-demand analytics tool given its open-source & free nature, advanced analysis and visualization abilities. Benefits of learning R with us:

Become proficient in manipulating, analyzing and visualizing data through the powerful R language

Relevant examples and case studies make the learning more effective and easier

Gain hands-on knowledge through the problem solving based approach of the course along with working on assignments and solving quizzes.

Today, R is being adopted by enterprise users for big data analytics and is increasingly being seen as a challenger to more traditional statistical and advanced analytic platforms.
Understand the basics of the R programming language and its capabilities for predictive analytics and data visualization

Learn how to manipulate, analyze, and visualize data using R

Gain hands-on knowledge through problem solving and working on assignments and quizzes

Learn about the various data types and data structures in R

Learn how to read and write data from various sources, including tabular data files and csv files

Learn how to perform basic statistics and statistical tests in R

Learn about data visualization techniques in R, including creating bar charts, scatter plots, and histograms

Learn about data manipulation techniques in R, including merging data frames, handling missing values and outliers, and data aggregation

Learn about the concepts of flow control, debugging tools, and functions in R

Learn about statistical modeling in R, including simple linear regression, multiple regression, logistic regression, clustering and PCA

Learn how to apply R in big data analytics and how it is increasingly being seen as a challenger to more traditional statistical and advanced analytic platforms.
No prerequisites.
Data Scientists

Business Analysts

Data Analysts

Those working in academia or science for tasks specifically involving statistical analysis.
Cybertronium Certification
Certified R Developer

Exam Platform: KALAM

Exam Format: Multiple Choice Question (MCQ)

Exam Questions: 25 Questions

Exam Duration is: 90 Minutes

Exam Pass Mark: 70%

Exam Fees: Inclusive in the Course Fees

Free Add-on: Free Membership access to KALAM Cybersecurity Collaboration & Community Skills Validation Platform
Module 1:   Introduction to R

What is R ?

Downloading and Installing R

Introduction to the R UI

Packages Management

Module 2:   Data & Data Types in R

Data Types

Reading and Writing data

Reading tabular data files

Reading from csv files

Creating a vector and vector operations

Initializing a data frame

Control structures

Selecting data frames by position and name

Changing directories

Module 3:   Statistics in R

Computing basic statistics

Comparing means of two samples

Testing a correlation for significance

Testing a proportion

Classical tests (t,z,F)

Summarizing Data

Cross tabulation

Module 4:   R Data Visualization

Creating a bar chart, dot plot

Creating a scatter plot, pie chart

Creating a histogram and box plot

Other plotting functions

Plotting with base graphics

Plotting with Lattice graphics

Plotting and coloring in R

Module 5:   Data Manipulation in R

Appending data to a vector

Combining multiple vectors

List management

Merging data frames

Data transformation

Strings and dates

Outlier detection

Handling NAs and Missing Values

Matrices and Arrays

Logical operations

Relational operators

Accessing Variables

Matrix Multiplication and Inversion

Managing Subset of data

Character manipulation

Data aggregation

Module 6:   Functions and Programming in R

Flow Control: For loop

If condition

While conditions and repeat loop

Debugging tools

Concatenation of Data

Combining Vars, cbind, rbind

Sapply, apply, tapply functions

Module 7:   Statistical Modelling in R

Simple linear regression

Multiple Regression model

Logistic regression

Hierarchical Clustering

K-Means Clustering

PCA for Dimensionality Reduction

CRD: Certified R Developer

OVERVIEW

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