Introduction to Data Mining
Data Mining Overview
Data Mining Issues
Data Mining Process
Basic Data Mining Tasks
Social Implications of Data Mining

Introduction to IBM SPSS Modeler in Data Mining
IBM SPSS Modeler Overview
Opening and Reading Data Files
Building and Saving Streams
Assessing Data Quality
Missing Data

Decision Trees
Decision Trees Overview
Decision Tree Algorithm
Actuarial Experiment (Building Decision Tree in IBM SPSS Modeler)
Model Interpretation

Regression Models
Regression Overview
Linear Regression vs Logistic Regression
Actuarial Experiment (Building Logistic Regression in IBM SPSS Modeler)
Model Interpretation

Neural Networks
Neural Network Overview
Actuarial Experiment (Building Neural Network in IBM SPSS Modeler)
Model Interpretation

Model Assessment
Comparison of Models
Model Scoring

Combining R and SPSS Modeler
R Basics
R nodes in IBM SPSS Modeler
Custom Dialog Builder
Actuarial Experiment

Q1 : What is the data mining software used in this course?
A1 : This course will be using SAS E Miner Software to analyze big database.

Q2 : Do I need to know any coding language in order to pass this course?
A2 : No. We will be using SAS E Miner with user friendly interface. Thus, no knowledge on coding language is needed.

Q3 : Will the database used in this course be given to each students?
A3 : Yes, all databases used in this course will be provided to all students.

Q4 : Do we need to download and install the software in our laptop/ computer?
A4 : No need because we will be using cloud version of SAS E Miner.