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IBM BAS-010日本語 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Preparation	- Data Transformation 1. Derived fields creation 2. Normalization and standardization - Data Integration 1. Merge and append operations 2. Data aggregation
Topic 2: Model Evaluation	- Model Assessment 1. ROC and lift charts 2. Confusion matrix interpretation - Model Comparison 1. Cross-validation 2. Model selection techniques
Topic 3: Deployment and Streams	- Model Deployment 1. Scoring models 2. Exporting models - SPSS Modeler Streams 1. Stream construction and execution 2. Node configuration and management
Topic 4: Model Building	- Predictive Modeling 1. Regression models 2. Classification models - Clustering Techniques 1. K-means clustering 2. Two-step clustering
Topic 5: Data Understanding	- Data Quality 1. Outlier detection 2. Missing value analysis - Data Exploration 1. Data profiling and summary statistics 2. Data types and structures in SPSS Modeler