Session 1

• R Studio Environment
• Console
• Assignment operator
• R Script
• Commenting
• Getting Help
• Data Types
• Vector
• List
• Matrices
• Factors
• Frames

Session 2

• File and Directory
• Reading Data
• Writing Data
• NA, NaN, inf
• Frames
• Control Structure
• Scope of variables

Session 3

• Packages to load data in R
• Date and Time functions
• Looping Functions
• Data Manipulation

Session 4

• Additional Functions
• Packages
• Data Visualization
• Regression Analysis
• Cluster Analysis

Practice Session

This course is taught in four sessions of four hours each. You should attend the instructor sessions as per the scheduled date and time. Video recordings for every lecture are added to the student dashboard. Archive videos from previous lectures are made available in the student dashboard as soon as a student enrolls for the class.

The course is delivered over the internet by an instructor through live web sessions.

Students are provided a web conference link allowing them to join the course on line at the scheduled date and time. Students have a choice of dialing in using a phone or using their computer microphone and speaker (or headset).

The course is divided into 4 lectures each consisting of 4 hours duration.  

The instructor sessions are recorded and made available to students from their on-line dashboard. This is helpful for students who miss a lecture or wish to revisit the lecture at their pace after the live sessions.

Further, students receive soft copies of a student guide, sample codes and answers to quiz and exercises. These are made available for download prior to the start of the first lecture on the course.Hands-on experience is provided by allowing access to Linux computers during the entire duration of the course. A discussion forum is available on-line to allow students to discuss between themselves as well as with the instructor. Access to recorded videos, course material and discussion forum is disabled one month after the delivery of the last lecture.Visit the FAQ page for commonly asked questions, feel free to submit a message, chat online with a specialist, request a call back  or simply call our corporate office at the number provided.

R is increasingly becoming popular and being adopted across multiple organizations and sectors of the industry. Being open source and free, demand for R is growing rapidly. It is increasingly being adopted by data scientists and analysts. Demand for R programmers is very good and there is great potential for growth in this language as BI, reporting and data analysis are becoming popular and beneficial for all sectors of industries.