Introduction to terms Business Intelligence, Business Analytics, Data, Information

How information hierarchy can be improved/introduced

Understanding Business Analytics and R

Knowledge about the R language, its community, and its ecosystem

Understand the use of 'R' in the industry

Compare R with other software in analytics

Install R and the packages useful for the course

Perform basic operations in R using the command line

Learn the use of IDE R Studio and Various GUI

Use the ‘R help’ feature in R

Knowledge about the worldwide R community collaboration

Install R and related packages

R operations using command line

IDE R-studio

R operations

Various kinds of data types in R and their appropriate uses

Built-in functions in R like seq(), cbind (), rbind(), merge()

Knowledge of the various subsetting methods

Summarize data by using functions like: str(), class(), length(), nrow(), ncol()

Use of functions like head(), tail() for inspecting data

Indulge in a class activity to summarize data

dplyr package to perform SQL join in R

Data Types in R

R Functions: seq(), cbind (), rbind(), merge(). str(), class(), length(), nrow(), ncol() head(), tail()

SQL joins in R

R Functions

dplyr package in R

Steps involved in Data Cleaning

Functions used in Data Inspection

Tackling the problems faced during Data Cleaning

Uses of the functions like grepl(), grep(), sub(), Coerce the data, uses of the apply() functions

Data Cleaning in R

Data Inspection in R

Data Coercion in R

R Functions: grepl(), grep(), sub(), apply()

Import data from spreadsheets and text files into R

Import data from other statistical formats like sas7bdat and spss, packages

Installation used for database import

Connect to RDBMS from R using ODBC

Basic SQL queries in R

Basics of Web Scraping

Database import

Connect to RDBMS using R

SQL queries in R

Web Scraping in R

Database import

R SQL queries

Web Scraping

Exploratory Data Analysis(EDA)

Implementation of EDA on various datasets

Boxplots

Understanding the cor() in R

EDA functions like summarize(), llist()

Multiple packages in R for data analysis

Fancy plots like the Segment plot, and HC plot in R

EDA using R

cor() in R

Plotting fancy graphs using R

EDA

Plotting Graphs

Data Visualization

Graphical functions present in R

Plot various graphs like tableplot, histogram, and Boxplot

Customizing Graphical Parameters to improvise plots

Understanding GUIs like Deducer and R Commander

Introduction to Spatial Analysis

Graphical Functions in R

Customizing Plots using R

Spatial Analysis

Data Visualization

GUIs

Spatial Analysis