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.