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2000+ Courses · 15+ Technology Domains
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Statistical Computing · Data Science · Research

Speak Fluently in

R Programming & Statistics

The language trusted by statisticians, researchers, and data scientists at Google, FDA, and NASA. Master data wrangling, advanced statistics, beautiful visualisations, and machine learning — the gold standard for analytical work.

ggplot2 tidyverse dplyr caret Shiny R Markdown Statistics ML in R
Enroll Now Brochure
r_analysis.R — Sales Forecast
Monthly Revenue Analysis (ggplot2)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
> ggplot(sales, aes(x=month, y=revenue)) +
  geom_bar(stat="identity", fill="#276DC3") +
  theme_minimal()
# Plot rendered successfully ✓
> summary(model)$r.squared
[1] 0.9473 # R² = 94.73%
12
Modules
65hrs
Duration
Cert
Included
65 hrs
Duration
Deep analytical focus
12
Modules
Statistics to ML
Viz
Expertise
ggplot2 mastery
Cert
Included
Industry recognised
Core Skills

8 R Programming Powers You'll Gain

The analytical toolkit used by researchers at universities, pharma giants, and hedge funds worldwide.

Data Visualisation

Create publication-quality charts with ggplot2 — histograms, scatter plots, heatmaps, and interactive plots with plotly.

Data Wrangling

Transform messy data into analysis-ready datasets using dplyr, tidyr, and the full tidyverse ecosystem.

Statistical Analysis

Hypothesis testing, ANOVA, regression, correlation — the full statistical toolkit for research and business.

Machine Learning

Classification, regression, clustering with caret and tidymodels — validated, production-ready ML pipelines.

R Markdown & Reports

Generate automated, reproducible reports combining code, analysis, and visualisations in HTML/PDF.

Shiny Web Apps

Build interactive data dashboards and web applications entirely in R — no JavaScript needed.

Database Integration

Query SQL databases, work with big data via Spark, and integrate R with data warehouses.

Functional R Programming

purrr, apply family, closures, environments, and writing clean, vectorised, production-grade R.

Packages & Tools
ggplot2
tidyverse
dplyr
data.table
caret/tidymodels
Shiny
R Markdown
plotly
purrr
sparklyr
Curriculum

12-Module R Programming Programme

From R syntax basics to building production Shiny apps and ML pipelines — complete analytical skill development.

  • R & RStudio setup
  • Vectors, matrices & lists
  • Data types & coercion
  • Control flow in R
  • Functions & environments
  • Data frames & tibbles
  • Factors & ordered factors
  • Strings with stringr
  • Dates & times with lubridate
  • Lists & nested structures
  • read.csv, readr, readxl
  • Connecting to SQL databases
  • JSON & XML handling
  • Web scraping with rvest
  • Writing R to CSV/Excel/database
  • filter, select, mutate, arrange
  • summarise & group_by
  • join operations (left, inner, full)
  • tidyr: pivot_longer, pivot_wider
  • Chaining with the pipe operator
  • Grammar of graphics concept
  • Geometric objects (geoms)
  • Aesthetic mappings & scales
  • Faceting & themes
  • Publication-quality charts
  • Descriptive statistics
  • Hypothesis testing (t-test, chi-square)
  • ANOVA & post-hoc tests
  • Correlation & covariance
  • Non-parametric tests
  • Simple & multiple linear regression
  • Logistic regression
  • Model diagnostics & residuals
  • Regularisation (LASSO, Ridge)
  • Interpreting model outputs
  • ML workflow in R
  • Train/test split & cross-validation
  • Classification algorithms
  • Regression algorithms
  • Model evaluation & tuning
  • ts objects & decomposition
  • ARIMA modelling
  • Forecasting with forecast package
  • Time series visualisation
  • Business forecasting application
  • R Markdown syntax
  • Dynamic documents
  • HTML, PDF & Word output
  • Parameterised reports
  • Automating analysis reports
  • Shiny reactive model
  • UI layout & components
  • Server-side logic
  • Shiny dashboards
  • Deploying Shiny apps
  • Functional programming with purrr
  • R performance optimisation
  • Rcpp & C++ integration
  • sparklyr for big data
  • Capstone: Complete analysis project
Course Snapshot
12 Modules
Full R stack
65+ Hours
Total learning
Download Available
Offline access
Certificate
On completion
Tech Support
Call / WhatsApp
Mon–Fri
9 AM – 6 PM
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Pricing & Packages

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Flexible pricing for every learning mode. Get a personalised quote in 24 hours.

Career Outcomes

High-Value Data Careers

Data Analyst (R)
₹5–15 LPA

Use R for business intelligence, dashboards, and automated reporting for executive decision-making.

Biostatistician
₹8–22 LPA

Apply statistical methods for clinical trials, pharma research, and public health studies.

Data Scientist (R)
₹8–28 LPA

Build ML models, conduct A/B tests, and develop predictive analytics systems using R.

Research Analyst
₹6–18 LPA

Academic and industry research requiring rigorous statistical analysis and peer-reviewed reporting.

Quant Analyst
₹12–35 LPA

Financial modelling, risk analysis, and algorithmic strategies built on R's statistical power.

BI Developer (Shiny)
₹7–20 LPA

Build interactive R Shiny dashboards for real-time business monitoring and data exploration.

New Batch Starting Soon — Limited Seats

Master R Programming & Data Science

Join pharma researchers, finance analysts, and data scientists using R to turn raw data into powerful insights and business decisions.

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