SAS Predictive Modeling

1. Advanced Analytics: Utilize statistical techniques and algorithms for predictive modeling.
2. Data Preparation: Preprocess and cleanse data to ensure quality for analysis.
3. Model Development: Build predictive models to forecast future outcomes.
4. Model Evaluation: Assess model performance using various metrics.

Before learning SAS Predictive Modeling, it's helpful to have the following skills:

1. Statistical Analysis: Understanding of statistical concepts and techniques.
2. Data Manipulation: Ability to manipulate and clean datasets using SAS or other tools.
3. Programming: Proficiency in SAS programming language for data analysis and modeling.
4. Data Visualization: Skill in visualizing data and model outputs to communicate insights effectively.

By learning SAS Predictive Modeling, you gain the following skills:

1. Data Preparation: Ability to preprocess and clean data for analysis and modeling.
2. Model Development: Proficiency in building predictive models using statistical techniques and algorithms.
3. Model Evaluation: Skill to assess model performance and interpret evaluation metrics.
4. Model Deployment: Capability to deploy models into production environments for real-time predictions.