r programming language in noida

 64 hours of blended learning

 10 real-life industry projects

 Dedicated mentoring session from industry experts

 Lifetime access to self-paced learning

Classroom Training

✔ Classroom training is considered the most effective form of learning.
✔ Develops important personality and career building skills.
✔ Technology-Based Learning. Common methods of learning via technology include.

Campus Training

✔ Online assessment program during campus placement.
✔ Campus learning is a premium option for campus instruction
✔ 24*7 learning assistance and support

Corporate House Training

✔ Flexible pricing options
✔ Enterprise grade Learning Management System (LMS)
✔ Enterprise dashboards for individuals and teams
✔ 24×7 learner assistance and support

Interactive Workshop

✔ A workshop is a great way for someone to learn about a particular subject.
✔ Workshop are usually longer often 1 to 2 days
✔ Seminars are usually 90 minutes to 3 hours
✔ A training workshop is a type of interactive training

Online Training

✔ Online training is effective for training across multiple locations.
✔ 24×7 learner assistance and support.
✔ Amirit Techservices online course platform is one of the most well-known sources of education via the internet.

R Programming Training

AMIRIT Techservices is the leading training institute in Northern India providing R Programming training as well as training in other cutting edge technologies. It is the best R programming Training in Delhi NCR. R is a programming language for statistical analysis, reporting, and graphics representation. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. Due to its expressive syntax and easy-to-use interface, it has grown in popularity in recent years.

Graduates who want to build career in this field.

  • Professionals working in data science and analytics industry.
  • Professionals looking for a career switch into data science and analytics.

Training in R programming is available on weekdays as well as weekends. Special Classes can also be scheduled as per requirement.


Module 1: Essential to R programming

• An Introduction to R
• History of S and R
• Introduction to R
• The R environment
• What is Statistical Programming?
• Why use a command line?
• Your first R session
• Introduction to the R language
• Starting and quitting R
• Recording your work
• Basic features of R
• Calculating with R
• Named storage
• Functions
• Exact or approximate?
• R is case-sensitive
• Listing the objects in the workspace
• Vectors
• Extracting elements from vectors
• Vector arithmetic
• Simple patterned vectors
• Missing values and other special values
• Character vectors
• Factors
• More on extracting elements from vectors
• Matrices and arrays
• Data frames
• Dates and times
• Built-in functions and online help
• Built-in examples
• Finding help when you don’t know the function name
• Built-in graphics functions
• Additional elementary built-in functions
• Logical vectors and relational operators
• Boolean algebra
• Logical operations in R
• Relational operators
• Data input and output
• Changing directories
• dump() and source()
• Redirecting R output
• Saving and retrieving image files
• Data frames and the read table function
• Programming statistical graphics
• High-level plots
• Bar charts and dot charts
• Pie charts
• Histograms
• Box plots
• Scatterplots
• QQ plots
• Choosing a high-level graphic
• Low-level graphics functions
• The plotting region and margins
• Adding to plots
• Setting graphical parameters
• Programming with R
• Flow control
• The for() loop
• The if() statement
• The while() loop
• Newton’s method for root finding
• The repeat loop, and the break and next statements
• Managing complexity through functions
• What are functions?
• Scope of variables
• Miscellaneous programming tips
• Using fix()
• Documentation using#
• Some general programming guidelines
• Top-down design
• Debugging and maintenance
• Recognizing that a bug exists
• Make the bug reproducible
• Identify the cause of the bug
• Fixing errors and testing
• Look for similar errors elsewhere
• The browser() and debug()functions
• Efficient programming
• Learn your tools
• Use efficient algorithms
• Measure the time your program takes
• Be willing to use different tools
• Optimize with care
• Simulation
• Monte Carlo simulation
• Generation of pseudorandom numbers
• Simulation of other random variables
• Bernoulli random variables
• Binomial random variables
• Poisson random variables
• Exponential random numbers
• Normal random variables
• Monte Carlo integration
• Advanced simulation methods
• Rejection sampling
• Importance sampling
• Computational linear algebra
• Vectors and matrices in R
• Constructing matrix objects
• Accessing matrix elements; row and column names
• Matrix properties
• Triangular matrices
• Matrix arithmetic
• Matrix multiplication and inversion
• Matrix inversion
• The LU decomposition
• Matrix inversion in R
• Solving linear systems
• Eigenvalues and eigenvectors
• Advanced topics
• The singular value decomposition of a matrix
• The Choleski decomposition of a positive definite matrix
• The QR decomposition of a matrix
• The condition number of a matrix
• Outer products
• Kronecker products
• apply()
• Numerical optimization
• The golden section search method
• Newton’Raphson
• The Nelder’Mead simplex method
• Built-in functions
• Linear programming
• Solving linear programming problems in R
• Maximization and other kinds of constraints
• Special situations
• Unrestricted variables
• Integer programming
• Alternatives to lp()
• Quadratic programming

Module 2: Data Manipulation Techniques using R programming

Module 3: Statistical Applications using R programming

1. What do I need to do to unlock my Amirit Techservices certificate?

2. Who provides the certification?

3. If I pass the Data Science – R Programming certification course exam, when and how do I receive my certificate?

1. What are the System Requirements?

2. Who are our instructors and how are they selected?

3. Is this live training, or will I watch pre-recorded videos?

4. What certification will I receive after completing the training?