R LANGUAGE

Eastpolesoft stands as a proactive, growth-oriented organization aiming at professional excellence with a pool of talented and dedicated work force. Our key

Schedule-1

What is R programming?
Advantages of R ?
What we can do with R?
Statistics using R?
Overview and History of R

Schedule-2

Installing R in Mac/Windows/Ubuntu
Installing R studio in Mac/Windows/Ubuntu
Setting up Working Directory for (Windows/Mac)
R Console Input and Evaluation

Schedule-3, 4

R Objects and Attributes
Vectors and Lists
Matrices
Factors
Missing Values
Data Frames
Reading Large tables, Reading Tabular data

Schedule -5

Subsetting – Basics
Subsetting – Lists
Subsetting – Matrices
Subsetting – DataFrames
Vectorized operations

Schedule -6

If-else
While
For
Repeat, Next, Break

Schedule-7

Loop Functions
Lapply
apply
mapply
tapply
split

Schedule-8

Generating Random Numbers
Simulating linear model
Random sampling

Schedule-9

Working with dplyr package

Schedule-10

Working with lubridate package

Schedule-11

Working with data.table package

Schedule-12

Working with ggplot2 (graphics) package

Schedule-13

Introduction to Machine Learning

Schedule-14

Mini-Project 1 (Data Wrangling)

Schedule-15

Mini-Project 2 ( Graphics using R)

Schedule-16

Mini-Project-13 (Linear Regression using R) – Machine Learning case study

Schedule-17

Creating an R package (Optional)

All the schedules will be for two days each 1 hour of class on first day followed by 2 days of lab on the next day. Schedule 17 would take 3 days. Each Mini Project will take three days time (Depends on Student though) Pre-Requsite: Having knowledge on Statistics can be helpful.