Reviews 4.9 (4.6k+)
Rated 4.7 out of 5
R Programming Certification Training
One of the top providers of online IT training worldwide is VISWA Online Trainings. To assist beginners and working professionals in achieving their career objectives and taking advantage of our best services, We provide a wide range of courses and online training.
About Course
🌐 R Programming Online Training – Course Overview
The R Programming Online Training course is designed to help learners master data analysis, statistical computing, and data visualization using the R programming language. This program covers both fundamental and advanced topics — from basic syntax and data structures to statistical modeling, machine learning, and predictive analytics.
Participants will gain hands-on experience in data wrangling, exploratory data analysis (EDA), and creating visual insights using ggplot2, dplyr, and tidyverse. You’ll also learn to integrate R with Excel, SQL, and Python for complete data workflows.
This course is ideal for Data Analysts, Statisticians, Business Intelligence Professionals, and aspiring Data Scientists looking to enhance their analytical skills and pursue data-driven roles in analytics and AI.
💡 Key Skills You’ll Learn
- R Programming fundamentals and syntax
- Data importing, cleaning, and transformation
- Statistical analysis and hypothesis testing
- Data visualization using ggplot2 and R Shiny
- Predictive modeling and machine learning basics
- R integration with SQL and Excel
- Real-time projects for business analytics
🎓 Certification Tracks
- R Programming Certification (Viswa Online Trainings)
- Data Analytics Certification using R
- R for Data Science Certification
- Advanced Statistical Programming Certification
R Programming Training Course Syllabus
Basic setup in R
- Loading Packages
- Installing Packages
- Unloading Packages
Basic Data Types in R Programming
- Integer
- Double
- Logical
- Character
Data Structures in R Programming
- Vectors
- Lists
- Matrix
- Data Frames
- Arrays
Loading of Data from Files
- CSV Files
- Excel Sheets
- Databases
- SAS Files
- SPSS Files
- STATA Files
- URL Etcs
Basic statistical Analysis
- Min, Max, Range
- Mean, Median
- variance,
- Standard Deviation
- Quantiles
- Categorical Values
Data Manipulation Package
- DPLYR
Data Cleansing Package
- TIDYVERSE
- TIDYR
Advanced-Data visualization
- ggplot2
- Lattice
R Programming Course Key Features
- Live Instructor based training with software
- Certification Oriented content
- Hands-on complete Realtime training
- Flexible schedule demo's & classes
- Live recorded videos access
- Study material provided
- JOB Assistance
Course completion certificate
R Programming Training - Upcoming Batches
Coming Soon
AM IST
Coming Soon
AM IST
Coming Soon
PM IST
Coming Soon
PM IST
Don't find suitable time ?
Request More Information
CHOOSE YOUR OWN COMFORTABLE LEARNING EXPERIENCE
Live Virtual Training
- Schedule your sessions at your comfortable with timings
- Instructor-Led training real time projects
- Certification Guidance
PREFERRED
Self-Paced Learning
- Complete set of live-online training session recorded videos.
- Learn technology at your own pace.
- Get access for lifetime.
Corporate Training
- Learn as a full day schedule with discussions, exercises.
- Practical use cases.
- Design your own syllabus based
FOR BUSINESS
R Programming Online Training FAQ'S
What is R Programming used for?
R is used for data analysis, statistical computing, visualization, and predictive modeling in data science and analytics.
What are R packages?
Packages are collections of functions and datasets that extend R’s capabilities — e.g., ggplot2, dplyr, caret, and tidyverse.
How does R differ from Python for data analysis?
R is preferred for statistical analysis and visualization, while Python excels in machine learning and automation.
What is a data frame in R?
A data frame is a table-like structure where each column contains values of one variable, and each row contains observations.
How do you handle missing data in R?
Missing data can be managed using functions like
na.omit(),is.na(), or by imputing values with statistical techniques.
Reviews
More Courses You Might Like
No posts found!