Business Analytics with R

A Practical Online course designed to make you an expert in Business Analytics & Intelligence.

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About The Course

This course is designed for professionals who aspire to learn 'R' language for Analytics. Practical approach of learning has been followed in order to provide a real time experience and make you think like an analyst. The course starts from the very basics like: Introduction to R programming, how to import various formats of Data, manipulate it, etc to some advanced R topics like: Data Mining Technique, performing Predictive Analysis to find optimum results based on past data, Data Visualisation using R Commander, Deducer, etc.

Course Objectives

After the completion of 'Business Analytics with R' at Edureka, you should be able to:

1. Understand the fundamentals of 'R'.

2. Get a broad insight into analytics and acquire skills in methodologies and techniques.

3. Get familiar with R Analytics as a career option with practical knowledge of some of the most in-demand techniques like Predictive Analytics, Association Rule Mining to perform prediction on the buyer's next purchase, Data Visualisation to plot, etc.

Who should go for this course?

This course is meant for all those students and professionals who are interested in working in industry analytics and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Business Analysts' in near future!

Pre-requisites

The pre-requisites for learning 'Business Analytics with R' include basic mathematics and good analytical skills. The good news is that - as this is an applied course, the focus will be on real-world case studies rather than just the theory.

Why Learn Business Analytics with R?

'Business Analytics with R' at Edureka will prepare you to:

1. Learn R programming language and use it in analytical projects including multiple industrial domains and scenarios.

2. Become an R user and learn to think like a data scientist/business analyst.

3. Get exposure into the latest analytics techniques including forecasting, social network analytics and text mining.

4. Add-on to your existing analytics knowledge and methodology.

5. Acquire advanced knowledge of analytics in web analytics, social media analytics and Industry norms.

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