Our R Program Online Training programs are designed for students, freshers, and working professionals who want to upskill and stay relevant. We offer R Program Online Courses that are practical, interactive, and aligned with the latest industry demands. Our R Programming Syllabus Covers the R syntax, data structures, data manipulation, exploratory data analysis, statistical methods, data visualization with ggplot2, and machine learning basics. Enroll now and learn from industry experts with flexible timings and get Job support.
R Programming Online Training
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DURATION
2 Months
EMI
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Mode
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Course Syllabus
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Fees, Duration & Batch Timings for R Programming
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2026
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
Course Fee
July 2026
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
Course Fee
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Syllabus of R Programming
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Module: 1 R Introduction
- Overview of R Programming
- Downloading and installing
- Help of Function
- Viewing documentation
- General issues in R
- Package Management
Module: 2 Data Inputting in R
- Data Types
- Subsetting
- Writing data
- Reading from csv files
- Creating a vector and vector operation
- Initializing data frame
- Control structure
- Re-directing R Output
Module: 3 Data Visualization
- Creating bar chart and dot plot
- Creating histogram and box plot
- Plotting with base graphics
- Plotting and coloring in R
Module: 4 Basic Statistic
- Computing Basic Statistics
- Comparing means of two samples
- Testing a proportion
- Data Munging Basics
Module: 5 Functions and Programming in R
- Flow control: For loop
- If condition
- Debugging tools
Module: 6 Data manipulation in R
- List Management
- Data Transformation
- Merging Data Frames
- Outlier Detection
- Combining multiple vectors
Module: 7 R an Database
- Performing queries
- RODBC and DBI Package
- Advanced Data handling
- Combined and restructuring data frames
Statistical Modelling in R
- Logical Regression
- Hierarchical Clustering PCA for Dimensionality Reduction
Objectives of R Programming
Our R Programming Online Training has the most up-to-date syllabus. The syllabus was curated by experts from the IT industry, who created this syllabus according to the current trends and standards in the IT industry, this makes the syllabus modern and reliable. The syllabus was also curated to serve students of all levels of experience thus, the syllabus covers topics from fundamental to advanced, some of the topics are discussed below:
- The syllabus begins with fundamental topics like, Overview of R Programming, Downloading and installing, Help of Function etc.
- The syllabus then moves a bit deeper into R Programming through topics like, Data Inputting in R, Data Types, Subsetting, Writing data etc.
- The syllabus then finally goes to advanced topics where students will learn about Data manipulation in R, Performing queries, RODBC and DBI Package etc.
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Why Softlogic Systems is the Best Choice for R Programming – Learn, Practice, and Get Placed!
Online & Offline Training Options
Learn at your convenience with flexible classroom and live online training.
Learn from 100+ Real-Time Developers
Get trained by industry professionals with years of hands-on experience.
Hands-on Projects & Codeathons
Practice with real-time projects and coding challenges to build confidence.
0% EMI Fee Options
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Get expert help with resume building, mock interviews, and soft skills.
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Access placement opportunities with leading MNCs and IT companies.
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Highlights of R Programming
What is R Programming?
R is an open-source programming language and environment favored by statisticians, data miners, and analysts for its extensive capabilities in statistical computing and graphics. With a rich collection of packages contributed by the community, it supports diverse statistical techniques like linear and nonlinear modeling, time-series analysis, classification, and clustering, making it a powerful tool for data analysis and visualization.
What are the reasons for learning R Programming?
The following are the reasons for learning R Programming:
- Statistical Analysis: R is great for analyzing data, like making models, testing theories, and studying relationships between variables.
- Data Visualization: With R, you can make really good visuals that show off what your data is saying, like charts and graphs.
Wide Adoption: Lots of different fields use R, like schools, companies, banks, and hospitals, so knowing it can open up lots of job opportunities.
What are the prerequisites for learning R Programming Online Training?
SLA does not demand any prerequisites for any courses as all the courses cover topics from fundamental to advanced level. However having a basic knowledge on these below topics can be beneficial in learning R Programming easily:
- Basic Computer Skills: Knowing how to use different types of computers (like Windows, macOS, or Linux) and managing files is important.
- Basic Programming Concepts: Understanding simple ideas in programming, like variables and loops, can make learning R easier.
- Mathematics and Statistics Fundamentals: Having a basic understanding of math, like adding and subtracting, and knowing some statistics helps with understanding how to use R for analyzing data.
Our R Programming Course is suitable for:
- Students
- Job Seekers
- Freshers
- IT professionals aiming to enhance their skills
- Professionals seeking career change
- Enthusiastic programmers
What are the course fees and duration?
The R Programming course fees depend on the program level (basic, intermediate, or advanced) and the course format (online or in-person).On average, the R Programming course fees come in the range of ₹25,000 to ₹30,000 INR for 2 months, inclusive of international certification. For some of the most precise and up-to-date details on fees, duration, and certified R Programming certification, kindly contact our Best Placement Training Institute in Chennai directly.
What are some of the jobs related to R Programming?
The following are some of the jobs related to R Programming:
- Data Analyst
- Data Scientist
- Statistical Analyst
- Research Analyst
What is the salary range for the position of Data Analyst?
The Data Analyst freshers salary typically with less than 1 year of experience earn approximately ₹4-5 lakhs annually. For a mid-career Data Analyst with around 3 years of experience, the average annual salary is around ₹5-6 lakhs. An experienced Data Analyst with more than 5 years of experience can anticipate an average yearly salary of around ₹8-9 lakhs. Visit SLA for more courses.
List a few real time R Programming applications.
Here are several real time R Programming applications:
- Stock Market Analysis
- Customer Segmentation
- Predictive Maintenance
- Sentiment Analysis
Boost Your Skills with Our R Programming Experts
Our Mentors are from Top Companies like:
The following are our trainer’s profile for the R Programming Online Training:
With over a decade of professional training experience, our R Programming instructors are skilled in:
- Fundamental R Programming concepts, such as data wrangling, cleaning, exploration, manipulation, plotting, and statistics.
- Using multiple tools and packages for exploratory and predictive analytics.
- Crafting sophisticated data visualizations to highlight insights and trends.
- Delivering engaging and interactive content.
- Employing various coaching and mentoring techniques for effective learning.
- Utilizing both RStudio IDE and command line interface proficiently.
- Troubleshooting R Programming code and demonstrating problem-solving skills.
- Applying best coding practices and guiding learners with coding basics.
- Collaborating closely with students and instructors to ensure a successful learning environment.
- Designing comprehensive lecture slides, course materials, and exercises for better comprehension and retention.
- Assisting students with resume building, interview preparation, and placement activities.
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What Modes of Training are available for R Programming?
Offline / Classroom Training
A Personalized Learning Experience with Direct Trainer Engagement!
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Training
Instructor Led Live Training! Learn at the comfort of your home
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
Corporate Training
Blended Delivery model (both Online and Offline as per Clients’ requirement)
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
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Hands-on Project Practices in R Programming
Recommendation System for E-commerce
Natural Language Processing (NLP) for Sentiment Analysis
Predictive Maintenance for Manufacturing
Anomaly Detection in Network Traffic
Customer Churn Prediction
Web Scraping and Text Analysis
Social Network Analysis
Time Series Forecasting for Energy Consumption
Market Basket Analysis
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FAQs
How many branches does SLA have?
Currently, SLA has two branches one is in Navalur, OMR and another is in K.K. Nagar.
What is special about SLA’s OMR branch?
SLA’s OMR branch is located in the middle of SLA’s IT hub where there is a lot of IT companies established, so this gives SLA a lot of credibility.
What is SLA’s policy on EMI?
SLA has EMI options available with 0% interest.
Does SLA have experienced trainers?
Yes, SLA has trainers who are experienced in both teaching and IT.
How does SLA resolve students’ issues?
SLA resolves students issues through the appointed HR officer.
What are some common data structures used in R for storing and manipulating data?
R commonly uses vectors, matrices, lists, and data frames to store and work with data, each serving different purposes for efficient data organization and analysis.
How can I install and manage R packages effectively?
You can install R packages with the install.packages() function, manage them using library() to load packages, and update or remove packages using update.packages() and remove.packages().
What are factors in R, and how are they useful in data analysis?
Factors in R represent categorical variables, where each level stands for a different category, aiding in statistical analysis, modeling, and visualization tasks involving categorical data.
How can I handle large datasets in R efficiently?
To manage large datasets efficiently in R, you can use tools like data.table and dplyr for quick data manipulation, store data in formats like Feather or Parquet for faster loading, and utilize parallel processing or distributed computing frameworks for parallelizing computations.
What are some best practices for organizing and documenting R code?
Best practices for organizing and documenting R code include using clear variable names, breaking code into reusable functions, adding comments and documentation within the code, maintaining a consistent coding style, and using version control systems such as Git for code management.
Additional Information for
the R Programming
Integration with Other Languages
R is being combined with languages such as Python and SQL to utilize the unique features of each for better data handling and analysis.
Machine Learning and Artificial Intelligence
R is heavily involved in machine learning and AI, offering sophisticated algorithms and tools for tasks like deep learning, natural language processing, and computer vision.
Big Data Analytics
R is adapting to handle large datasets by incorporating big data technologies like Apache Spark and Hadoop, enabling distributed computing for efficient analysis using packages like SparkR and sparklyr.
Interactive Data Visualization
The demand for dynamic and interactive data visualization is increasing, leading to the creation of packages like Plotly, Shiny, and ggplot2 extensions, allowing users to create engaging plots and dashboards directly within R.
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