Overview
4h 55m | 33 Videos | 65729 Views | 
All Levels| English[Auto-generated] Data Science and Machine Learning with R (Part #1) – Understanding R
In the recent years R has become the widely used programming language for computational statistics, visualization and data science. R is used by many statisticians, scientists and data analysts to find a solution for their problem in various fields. R is used as the most important tool for business analytics in companies like Google, Facebook and LinkedIn. R contains every data analytics techniques at your fingertips. It helps you to perform some of the most commonly performed tasks by business analysts with the help of its 4000 packages.
Through this course we will learn about course introduction, course curriculum, discriminant analysis, introduction to r & analytics, evolution of business analytics, business example- hotel, data for business analytics, ordinal data, decision model example, descriptive decision models, business analytics life cycle, model deployment, steps in problem solving process, software used in business analytics, getting started with r, installing r studio, basics of r & function, data types, recycling rule, special numerical values, parallel summary functions, logical conjunctions, pasting strings together, type coercion, array & matrix, factor, repository & packages, installing a package, importing data, importing data spss, working with data and data aggregation.
Target Customers:
This course will be useful for students and Data analysts and people from Analytics domain. It will also be useful for people who wanted to learn business analytics using R.
Pre-Requisites:
The pre requisites for this course include basic knowledge of statistics. Knowledge in any other programming language is an added advantage but not a must.
