Introduction to Business Analytics

Course Overview

Introduction to Predictive Modeling: Predictive Modeling Fundamentals and Decision Trees

1. Introduction.
2. Cultivating Decision Trees
3. Optimising the Complexity of Decision Trees
4. Understanding Additional Diagnostic Tools
5. Autonomous Tree Growth Options

Data Preparation & Exploration using SAS:

1. Importing and Exporting Excel files ,CSV Files, SAS data files
2. Data Preparation – Modifying & Correcting Source Data,
3. Input Transformations – Imputation, Detecting Outliers
4. Plotting & Interpreting Graphs, Bar Plot, Pie Chart, Scatter Plot, Histogram, Labeling the plots, Giving different colours and formatting charts, Data imputing, Data Wrangling, Partitioning Data

 Introduction to Predictive Modeling: Regressions

1. Selecting regression inputs
2. Optimizing regression complexity.
3. Interpreting regression models.
4. Transforming inputs.
5. Categorical inputs.
6. Polynomial regressions

 Advanced Predictive Models

1.  Describe the basics of support vector machines
2.  Use the HP Forest node in SAS Enterprise Miner to fit a forest model
3.  Modeling rare events
4.  Use the Rule Induction node in SAS Enterprise Miner

Machine Learning using SAS:Text Analytics & Model Assessment & Deployment

1. Text Analytics, Comparison Multiple Models,
2.  Champion Models, Running Features of Scoring, 
3. Running a Scoring Test in Model Manager