Syllabus

Business Data Analytics

1. Introduction to Business Data Analytics
2. Business Case for Using Analytics
3. Understanding Data
4. Business Analytics, Business Intelligence and Data Mining
5. Analytical Decision Making
6. Analysing Business Problems
7. Skills of a Good Business Analyst
8. Future of Business Analytics
9. Big Data in the Enterprise
10. Social Media Analytics
11. Basic Statistical Concepts

R Programming
1. INTRODUCTION TO R
History of R
Features of R
2. ENVIRONMENT SETUP
Installation of R and R-Studio
Local Environment Setup
3. R FUNDAMENTALS
Comments
Command Prompt
Script File
4. DATA TYPES
Vectors
Lists
Matrices
Arrays
Factors
Data Frames
5. VARIABLES
Variable Assignment
Data Type of a Variable
Finding Variables
Removing Variables
6. OPERATORS
Types of Operators
Arithmetic Operators
Relational Operators
Logical Operators
Assignment Operators
Other Operators
7. CONDITIONAL STATEMENTS
If Statement
If...Else Statement
The if...else if...else Statement
Switch Statement
8. LOOPING
Repeat Loop
While Loop
For Loop
Loop Control Statements
Break Statement
Next Statement 9. FUNCTION
Function Definition
Function Components
Built-in Function
User-defined Function
Calling a Function
Lazy Evaluation of Function
10. STRINGS
String Construction Rules
String Manipulation
11. VECTORS
Vector Creation
Accessing Vector Elements
Vector Manipulation
12. LISTS
Creating a List
Naming List Elements
Accessing List Elements
Manipulating List Elements
Merging Lists
Converting List to Vector
13. MATRICES
Accessing Elements of a Matrix
Matrix Computations
14. ARRAYS
Naming Columns and Rows
Accessing Array Elements
Manipulating Array Elements
Calculations Across Array Elements
15. FACTORS
Factors in Data Frame
Changing the Order of Levels
Generating Factor Levels
16. DATA FRAMES
Extract Data from Data Frame
Expand Data Frame
17. PACKAGES
18. DATA RESHAPING
Joining Columns and Rows in a Data Frame
Merging Data Frames
Melting and Casting
Melt the Data
Cast the Molten Data
19. CSV FILES
Getting and Setting the Working Directory
Input as CSV File
Reading a CSV File
Analyzing the CSV File
Writing into a CSV File
20. EXCEL FILE
Install xlsx Package
Verify and Load the "xlsx" Package
Input as xlsx File
Reading the Excel File
21. BINARY FILES
Writing the Binary File
Reading the Binary File
22. XML FILES
Input Data
Reading XML File
Details of the First Node
XML to Data Frame
23. JSON FILE
Install rjson Package
Input Data
Read the JSON File
Convert JSON to a Data Frame
24. WEB DATA
25. DATABASES
RMySQL Package
Connecting R to MySql
Querying the Tables
Query with Filter Clause
Updating Rows in the Tables
Inserting Data into the Tables
Creating Tables in MySql
Dropping Tables in MySql
26. PIE CHARTS
Pie Chart Title and Colors
Slice Percentages and Chart Legend
3D Pie Chart
27. BAR CHARTS
Bar Chart Labels, Title and Colors
Group Bar Chart and Stacked Bar Chart
28. BOXPLOTS
Creating the Boxplot
Boxplot with Notch
29. HISTOGRAMS
Range of X and Y values
30. LINE GRAPHS
Line Chart Title, Color and Labels
Multiple Lines in a Line Chart
31. SCATTERPLOTS
Creating the Scatterplot
Scatterplot Matrices
32. MEAN, MEDIAN & MODE
Mean
Applying Trim Option
Applying NA Option Median
Mode
33. LINEAR REGRESSION
Steps to Establish a Regression
lm() Function
predict() Function
34. MULTIPLE REGRESSION
lm() Function
Example
35. LOGISTIC REGRESSION
Create Regression Model
36. NORMAL DISTRIBUTION
dnorm()
pnorm()
qnorm()
rnorm()
37. BINOMIAL DISTRIBUTION
dbinom()
pbinom()
qbinom()
rbinom()
38. POISSON REGRESSION
39. ANALYSIS OF COVARIANCE
40. TIME SERIES ANALYSIS
Different Time Intervals
Multiple Time Series
41. NONLINEAR LEAST SQUARE
42. DECISION TREE
43. RANDOM FOREST
44. SURVIVAL ANALYSIS
45. CHI SQUARE TEST