Complete Data Science using R programming

Build predictive engines, multi-class classifiers, recommendation models to up-sell and cross-sell business products


This course facilitates major part of a Data Science project activity. The program is divided into three major parts. Part One demonstrates the core syntactical skills needed to code and program using R programming. It covers writing basic to advanced R programs for data science. Part two demonstrates the needed statistics to understand the interpretation that comes out of a statistical data analysis and model making. It helps tune your machine learning model parameters better. The third part is machine learning. You will use previously learnt two parts to build predictive engines for business decision making, classifiers to automate a mundane task and finally a recommendation model to up-sell & cross-sell business products to consumers.


TECHNOLOGY USED: R core programming, Machine Learning for R

What Will I Learn?

  • Learn to program using R for data science
  • Learn to create data structures for machine learning in R
  • How to render visuals charts and their interpretations in R
  • Use Native statistics modules in R
  • Build data reasoning

Topics for this course

52 Lessons40h

Introduction to the Course

How to use R to explore and visualize data
How to use randomization and simulation to build inferential ideas
How to effectively create stories using the ideas to convey information to audience
Introduction to data sources in R (built-in)
What is a data science pipeline?

Introduction and Installation

Data Structures in R





About the instructors

Pedagogy Trainings

4.67 ratings (6 )
23 Courses
80 students



Course Details


  • Python Core for Analytics

Target Audience

  • IT Managers
  • Professionals
  • Students
  • ML Enthusiast