A00-240

The SAS A00-240 exam, "SAS Certified Specialist: Predictive Modeling using SAS Enterprise Miner 14", focuses on the practical application of SAS Enterprise Miner for predictive modeling. The main points covered include:

1. Data Exploration and Preparation:

• Data understanding and summarization: Creating descriptive statistics, identifying data quality issues (missing values, outliers), and visualizing data distributions.
• Data cleaning and transformation: Handling missing data (imputation techniques), outlier treatment, variable transformation (e.g., log transformation, standardization).
• Feature engineering and selection: Creating new variables from existing ones and selecting the most relevant variables for the model.

2. Model Building and Evaluation:

• Understanding different modeling techniques: This is a crucial aspect and covers a wide range of algorithms, including:
  • Regression: Linear regression, logistic regression.
  • Decision Trees: CART, CHAID.
  • Neural Networks: Multilayer perceptrons.
  • Ensemble methods: Boosting, bagging (random forests).
  • Support Vector Machines (SVMs):
• Model building process within SAS Enterprise Miner: Knowing how to implement these algorithms within the EM environment, including setting parameters and interpreting results.
• Model assessment and validation: Using appropriate metrics (e.g., AUC, lift charts, accuracy, precision, recall, F1-score, RMSE) to evaluate model performance and avoid overfitting. Understanding techniques like cross-validation.

3. Deployment and Reporting:

• Model deployment options: Understanding how to deploy a model for use in a production environment. This may involve creating score code or using other deployment tools.
• Creating reports and visualizations: Communicating model results effectively using SAS Enterprise Miner's reporting capabilities. This includes creating visualizations to explain the model's predictions and insights.

4. Specific SAS Enterprise Miner functionalities:

• Using the nodes within SAS Enterprise Miner: A significant portion of the exam focuses on navigating the graphical user interface and understanding the function of different nodes within the data mining process. You'll need to know how to connect nodes, configure parameters, and interpret the output from each node.
• Understanding the process flow: The ability to build a complete predictive modeling workflow from data import to model deployment is key.

In summary: The A00-240 exam doesn't require deep theoretical knowledge of each algorithm, but it heavily emphasizes the practical application of these algorithms within the SAS Enterprise Miner environment. Understanding the process flow, interpreting results, and effectively communicating model findings are key to success. Focus on hands-on experience and practice using SAS Enterprise Miner.