R Programming Language
Master R Programming Language skills and take your career to the next level! Learn R fundamentals, statistical programming, inheritance, polymorphism, exception handling, collections, networking and RMySQL / DBI through a structured R programming training program.
Learn R Programming Language at NIPSTec
The R Programming Language Course at NIPSTec is designed to help learners build a foundation in R programming and object-oriented development. This 2-month, 40+ hour offline training program covers R fundamentals, decision making and loops, vectors, lists, matrices and data frames, inheritance, polymorphism, abstraction, encapsulation and more.
Learners explore arrays, strings, exception handling, R input and output, collections, networking, date and time, AWT, Swing, Applet concepts, LayoutManager and RMySQL / DBI with MySQL.
NIPSTec offers industry-relevant training supported by qualified and experienced trainers, structured learning, pre-training assessment and post-training evaluation.
R Programming Language Course Highlights
R Programming Fundamentals
Understand R history, features, variables, data types, keywords, operators and the basics of writing R programs.
Object-Oriented Programming
Learn R data types, vectors, lists and data frames, static and this keywords, naming conventions and R OOP concepts.
Statistical Analysis & Data Visualization
Explore inheritance, aggregation, overloading, overriding, super and final keywords, runtime polymorphism and dynamic binding.
Regression & Hypothesis Testing
Understand abstract classes, interfaces, packages, access modifiers and encapsulation in R.
Statistical Analysis & Data Structures
Work with R exceptions, try-catch, throw and throws, Vectors, Lists, List, Matrices, Collection and Iterator.
Data Import & Export & Database Connectivity
Explore networking concepts, socket programming, date and time, RMySQL / DBI driver concepts and connectivity with MySQL.
R Programming Language Course Overview
This R programming training program progresses from R fundamentals and decision making and loops to statistical programming, inheritance, exception handling, collections, data input and output, networking, data visualization and database connectivity using RMySQL / DBI and MySQL.
R Programming Language Course Curriculum
Explore the R Programming syllabus, including programming fundamentals, data analysis concepts, collections, networking, data visualization and database connectivity.
Module 1Introduction to R ⌄
- What is R?
- Features and applications of R
- Installing R and RStudio
- RStudio interface
- R Console and R Script
- Comments in R
Module 2R Data Types, Input & Output ⌄
- Numeric, Integer, Character, Logical, Complex and Raw types
- Checking data types with class(), typeof(), is.numeric(), is.character() and is.logical()
- print(), cat() and readline()
- Type conversion
- Taking numeric and multiple inputs
Module 3Operators, Decision Making & Loops ⌄
- Arithmetic, relational, assignment, special and logical operators
- %in%, modulus and integer division
- if, if...else, if...else if...else, nested if and switch()
- for, while and repeat loops
- break and next
Module 4R Functions & Strings ⌄
- R functions and function arguments
- Built-in functions
- Creating and concatenating strings
- paste() and paste0()
- nchar(), toupper(), tolower(), substr() and substring()
- gsub() and regular expressions
Module 5Vectors, Lists & Arrays ⌄
- Creating vectors with c(), seq() and rep()
- Vector indexing and slicing
- Creating lists; accessing elements; named and nested lists
- List manipulation and adding/removing elements
- Vector operations, named vectors and sorting
- head(), tail(), str() and summary()
- One-dimensional, two-dimensional and multidimensional arrays
- Array indexing and operations
Module 6Matrices, Factors & Data Frames ⌄
- Creating matrices; rows and columns
- Matrix addition, subtraction and multiplication
- Matrix indexing, transpose, inverse, apply() and determinant
- Categorical data and factors
- Creating factors, levels, ordered factors, factor() and levels()
- Creating data frames; accessing rows and columns
- Adding/removing columns, filtering/updating records, merging data frames and sorting data
Module 7Statistical Analysis & Probability ⌄
- Mean, median, mode and range
- Variance, quartiles, percentiles and standard deviation
- Covariance and correlation
- Probability and normal distribution
- Binomial distribution and sampling
Module 8Hypothesis Testing & Advanced Statistics ⌄
- Hypothesis testing: null and alternative hypotheses
- p-value and t-test
- Chi-square test
- ANOVA
- Correlation test
- Confidence intervals
Module 9Regression Analysis ⌄
- Simple linear regression
- Multiple linear regression
- lm()
- Regression coefficients and R-squared
- Prediction and model evaluation
Module 10Data Visualization with ggplot2 ⌄
- Introduction to ggplot2
- Pie chart, bar chart and line chart
- Scatter plot, histogram and box plot
Module 11File Handling & Data Import/Export ⌄
- CSV, Excel and text files
- Reading and writing files
- Import/export formats: CSV, Excel, XML, SQL/MySQL and JSON
Module 12R with MySQL ⌄
- Connecting R to MySQL
- Reading database tables
- Inserting and updating records
- Running SQL queries from R
- Common packages: RMySQL and DBI
Tools & Technologies You'll Learn
Explore R programming concepts and technologies included in the R Programming Language course, from statistical programming to networking, data visualization and database connectivity.
Career Opportunities After R Programming Training
R Programming programming skills can support learners who want to explore entry-level software development and programming opportunities. Career paths depend on individual skills, practical experience and employer requirements.
R Developer
Apply R R programming fundamentals and object-oriented concepts in software development tasks.
Junior Software Developer
Build foundational programming skills relevant to junior-level software development roles.
Software Development Trainee
Develop programming knowledge for trainee-level software development opportunities.
Programming Trainee
Strengthen R fundamentals and learn to work with structured programming concepts.
Application Development Trainee
Explore application development fundamentals, R data visualization and database connectivity.
R Application Support
Use foundational R knowledge in suitable application support and technical roles.
Learning & Practical Support
Structured Learning
Progress through R fundamentals, OOP concepts, collections, networking and database connectivity.
Offline Classroom Training
Attend the 2-month, 40+ hour R Programming program in offline classroom mode.
Pre-Training Assessment
Assess current skills and learning needs before beginning the training journey.
Expert-Led Classes
Learn with qualified and experienced trainers through a structured training approach.
R Programming Topics
Study OOP, exception handling, collections, data input and output, networking and RMySQL / DBI concepts.
Post-Training Evaluation
Review learning progress and evaluate the skills developed during training.
Why Choose NIPSTec for R Programming Training?
With over 25+ years of experience in training students and corporates, NIPSTec delivers training across India for learners, professionals, corporates and government departments. Its training approach includes qualified and experienced trainers, industry-relevant curriculum, job-oriented programs and structured learning support.
25+ Years of Experience
Experience in training students and corporates.
Qualified & Experienced Trainers
Training led by qualified and experienced trainers.
Industry-Relevant Curriculum
A structured curriculum covering relevant R topics.
Job-Oriented Programs
Training programs designed around practical skill development.
PAN India Reach
Training and development services across India.
ISO 9001:2015 Certified
NIPSTec is an ISO 9001:2015 certified company.
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R Programming Language FAQs
Common questions about the R Programming Language course
What is the duration of the R Programming Language course?
The R Programming Language course is listed as a 2-month, 40+ hour training program.
Is the R Programming training conducted offline?
Yes. The course brochure specifies offline mode of training.
What topics are covered in the R Programming Language syllabus?
The curriculum includes R basics, data types, input/output, operators, decision making, loops, functions, strings, vectors, lists, arrays, matrices, factors, data frames, statistical analysis, hypothesis testing, regression, ggplot2 visualization, file handling, data import/export and R with MySQL.
Does the course cover R OOP concepts?
Yes. Topics include R data types, vectors, lists and data frames, inheritance, aggregation, overloading, overriding, runtime polymorphism, dynamic binding, abstraction and encapsulation.
Does the R Programming Language course include R Data Structures?
Yes. The listed collection topics include Vectors, Lists, Lists, Matrices, Collection and Data Frames.
Will I learn R exception handling?
Yes. The curriculum includes R exceptions, try-catch, multiple catch blocks, nested try, and throw and throws keywords.
Does the course cover R networking?
Yes. Data Import & Export concepts and socket programming are included, along with date and time topics such as DateFormat, SimpleDateFormat and getting the current date and time.
Does the course include RMySQL / DBI and MySQL?
Yes. The curriculum includes basic RDBMS concepts, RMySQL / DBI driver and database connectivity steps, and connectivity with MySQL.
Does the course cover R AWT and Swing?
The listed Data Visualization topics include AWT basics, buttons, labels, text fields, checkboxes, Applet concepts, graphics, event handling, ActionListener, MouseListener and KeyListener. Swing and LayoutManager topics are also listed.
Where is NIPSTec's training centre located?
D-82, First Floor, Malviya Nagar, New Delhi - 110017, India.
How can I enquire about the R Programming Language course?
You can use the enquiry form on this page or contact NIPSTec at +91-9971091034 or nipstec@nipstec.com for course information.