IBM C2020-012日本語 Exam Details & Actual Exam Questions

  • Exam Code/Number: C2020-012日本語
  • Exam Name/Title: IBM SPSS Modeler Data Analysis for Business Partners v2 (C2020-012日本語版)
  • Certification Provider: IBM
  • Corresponding Certification: IBM Certified Associate
  • Exam Questions: 25
  • Updated On: Sep,11 2026
  • Certification Level: Professional

IBM SPSS Modeler Data Analysis for Business Partners v2 (C2020-012日本語版) Exam Questions

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This exam has been stopped to register, new exam code replace: C2090-012J

IBM C2020-012日本語 Exam Overview:

Certification Vendor:IBM
Exam Name:IBM SPSS Modeler Data Analysis for Business Partners v2
Exam Number:C2020-012
Passing Score:Not publicly disclosed
Exam Duration:90 minutes
Exam Format:Scenario-based questions, Multiple choice
Exam Price:Varies by region (approximately USD $200)
Available Languages:English
Certificate Validity Period:3 years (typical IBM certification validity)
Real Exam Qty:50-60
Sample Questions:IBM C2020-012日本語 Sample Questions
Exam Way:Online proctored exam or authorized test center
Pre Condition:Recommended experience with data analysis and SPSS Modeler; no strict formal prerequisite required
Official Syllabus URL:https://www.ibm.com/training/certification

IBM C2020-012日本語 Exam Syllabus Topics:

SectionObjectives
Modeling Techniques in IBM SPSS Modeler- Predictive modeling
  • 1. Clustering methods
    • 2. Regression models
      • 3. Classification models
        - Model building workflow
        • 1. Stream design using SPSS Modeler nodes
          • 2. Feature selection and engineering
            Model Evaluation and Validation- Evaluation techniques
            • 1. Cross-validation methods
              • 2. Training and testing datasets
                - Performance metrics
                • 1. Accuracy, precision, recall
                  • 2. ROC curve and lift charts
                    Data Understanding and Preparation- Data quality and preprocessing
                    • 1. Handling missing values and outliers
                      • 2. Data cleaning and transformation techniques
                        - Data import and integration
                        • 1. Importing structured and unstructured data sources
                          • 2. Connecting to databases and files
                            Deployment and Operationalization- Model deployment
                            • 1. Integration into business systems
                              • 2. Exporting predictive models
                                - Monitoring and maintenance
                                • 1. Model performance tracking
                                  • 2. Updating models with new data
                                    IBM SPSS Modeler Workflow Concepts- Stream creation and management
                                    • 1. Node-based workflow design
                                      • 2. Data flow orchestration


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