| Unit 1 [Book] | |
| Data Processing for Predictive Analysis | VIEW |
| Data Transformation | VIEW |
| Min-Max Normalization | VIEW |
| Z- Score Standardization | VIEW |
| Transformations to Achieve Normality | VIEW |
| Graphical and Numerical Methods for identifying outliers | VIEW |
| Unit 2 [Book] | |
| Predictive Analytics | VIEW |
| Multiple Regression and Model Building | VIEW |
| Logistic Regression | VIEW |
| Neural Networks | VIEW |
| Naïve Bayes and Bayesian Networks | VIEW |
| Model Evaluation Techniques | VIEW |
| Unit 3 [Book] | |
| Introduction to Big Data & Analytics: What is Big Data? | VIEW |
| Characteristics and Evolution of Big Data | VIEW |
| Traditional Business Intelligence (BI) Versus Big Data | VIEW |
| Terminologies used in Big Data Environments | VIEW |
| Analytics Flow for Big Data, Big Data Stack | VIEW |
| Unit 4 [Book] | |
| Big Data Analytics | VIEW |
| Working with big data analytics tools: NoSQL, Hadoop, MapReduce, MongoDB and Cassandra | VIEW |
| Hands-on practical learning on these tools | VIEW |