In this course, students will learn beginner and intermediate levels of data science with R. Students are expected to complete 16 modules of course work over 8 weeks and 2 projects that demonstrate the skills accquired. Free pre-requisite online course work is available for those interested. After completing this course, students are expected to gain expertise in machine learning algorithms such as decision trees, cluster analysis and regression.
There is no specific pre-requisite for Data Science with R. However, a basic understanding of statistics and R can be beneficial. The course is offered only in English language.
Saturday & Sunday; 8 AM - 11 AM IST
The course is delievered online.
48 Hours of Online Live Instructor-led Classes
Weekend class: 16 sessions of 3 hours each
Weekday class: 24 sessions of 2 hours each
Our student advisors will work with you to build a portfolio
of projects to showcase your newly mastered skills. Projects
include a mix of real world and simulated case studies
24 x 7 Support
Whether it is query related to the course or otherwise,
we got your back. Our experts are availabe 24 X 7 to
answer your queries
Quiz & Assignments
Each module of the course includes interactive tutorials,
quiz, assignments and case studies that help sharpen your
skills and aid in building your project portfolio
Our learning management system will give you lifetime
access to all course related resources such as videos,
slides, interactive tutorials, quiz and assignments
You have mastered the skills, built your portfolio. Earn a
valued certificate and get help in crafting a professional
CV as well as resources and guidance for interviews
Learning Objectives - Get an introduction to and quick tour of R, RStudio and GitHub.
Learning Objectives - Learn to read/import data into R and the grammar of data manipulation.
Learning Objectives - Learn to handle date/time, strings in R and advanced data visualization.
Learning Objectives Get an introduction to descriptive statistics, statistical distributions and statistical inference.
Learning Objectives Get an introduction to linear and logistic regression.
Learning Objectives Get an introduction to supervised and unsupervised learning techniques and implementation of decision trees and cluster analysis.
Learning Objectives Get an introduction to text mining and sentimental analysis.
This course will give you an introduction to data science using R. It will teach you the skills needed for data science. You will learn how to read data into R, clean the data, structure and transform it accordingly, explore the data using visualization and finally model it using different techniques. The course also covers version control, literate programming and reproducible research.
Data science with R course is designed to offer you an introduction to data science. The course offers:
Data science with R course is designed to offer you an introduction to data science. This course will introduce you to:
Our course is designed to cater to the needs of a wide range of audience. It is best suited for:
There is no specific pre-requisite for Data Science with R. However, a basic understanding of statistics and R can be beneficial. The course is offered only in English language. We offer several free self paced courses when you enroll for this course.
Your system should have minimum 4GB RAM or above.
All assignments will be should be completed using RStudio IDE and shared on a GitHub repository. The step-wise installation guides for setting up the environment on various operating systems are present in the LMS. In case you come across any doubt, the 24*7 support team will promptly assist you.
Towards the end of the course, you will be working on a live project. You can choose any of the following as your project work:
While we do not promise jobs, we work with our students in designing resumes and sharing it with our corporate clients and hiring partners. Students who dedicate time to build a portfolio of projects have found success in getting jobs.
Yes, we offer a 20% discount for students. You need to use the email provided by your university/college or after the enrolment, you can send us a copy of your identity card from your university/college email id. Post verification, we refund 20% of the course fee.
There is no need to worry about missing classes as we offer you the following choices:
The live classes are held on weekends and we expect the students to spend another 10 hours during the rest of the week to keep up with the course. Since it might not be possible to spend such time week after week for 8 weeks, we offer post course support to ensure that you can complete the projects and your learning outcome is maximized.
Once you make the payment, you get immediate access to course materials in the LMS. It will include recordings from the previous batch, installation guides and suggested readings. You also get access to whole set of free self paced courses.
You can use any of the following options for doubt clearance:
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrolment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.