CH 01 – Introduction to Business Analytics

·         Overview

·         Business Decisions and Analytics

·         Types of Business Analytics

·         Applications of Business Analytics

·         Data Science Overview

·         Conclusion

CH 02 – Introduction to R Programming

·         Overview

·         Importance of R

·         Data Types and Variables in R

·         Operators in R

·         Conditional Statements in R

·         Loops in R

·         R script

·         Functions in R

·         Conclusion

CH 03 – Data Structures

·         Overview

·         Identifying Data Structures

·         Demo: Identifying Data Structures

·         Assigning Values to Data Structures

·         Data Manipulation

·         Demo: Assigning Values and Applying Functions

·         Conclusion

CH 04 – Data Visualizations

·         Overview

·         Introduction to Data Visualization

·         Data Visualization Using Graphics in R

·         Ggplot2

·         File Formats of Graphic Outputs R

·         Conclusion

CH 05 – Statistics for Data Science

·         Overview

·         Introduction to Hypothesis

·         Types of Hypothesis

·         Data Sampling

·         Confidence and Significance Levels

·         Hypothesis Test

·         Parametric Test

·         Non-Parametric Test

·         Hypothesis Tests about Population Means

·         Hypothesis Tests about Population Variance

·         Hypothesis Tests about Population Proportions

·         Conclusion

CH 06 – Regression Analysis

·         Overview

·         Introduction to Regression Analysis

·         Types of Regression Analysis Models

·         Linear Regression

·         Demo: Simple Linear Regression

·         Non-Linear Regression

·         Demo: Regression Analysis with Multiple Variables

·         Cross Validation

·         Non-Linear to Linear Models

·         Principal Component Analysis

·         Factor Analysis

·         Conclusion

CH 07 – Classification

·         Overview

·         Classification and Its Types

·         Logistic Regression

·         Support Vector Machines

·         Demo: Support Vector Machines

·         K-Nearest Neighbours

·         Naive Bayes Classifier

·         Demo: Naive Bayes Classifier

·         Decision Tree Classification

·         Demo: Decision Tree Classification

·         Random Forest Classification

·         Evaluating Classifier Models

·         Demo: K-Fold Cross Validation

·         Conclusion

CH 08 – Clustering

·         Overview

·         Introduction to Clustering

·         Clustering Methods

·         Demo: K-means Clustering

·         Demo: Hierarchical Clustering

·         Conclusion

CH 09 – Association

·         Overview

·         Association Rule

·         Apriori Algorithm

·         Demo: Apriori Algorithm

·         Conclusion