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CertNexus DSP-210 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Extracting, Transforming, and Loading Data | 17-25% | - Collect and integrate data from relevant sources - Clean, transform, validate, and prepare datasets |
| Defining the Need to Be Addressed Through Data Science | 7-9% | - Define the business problem and data science objectives - Identify relevant data sources, stakeholders, and success criteria |
| Testing Models | 4-7% | - Validate results and assess model limitations - Evaluate model performance using appropriate metrics |
| Communicating Findings | 4-7% | - Present findings through reports and visualizations - Communicate insights, limitations, and recommendations to stakeholders |
| Building Models | 19-27% | - Select and train appropriate statistical or machine learning models - Prepare training, testing, and validation datasets - Tune model parameters and compare model performance |
| Operationalizing the Pipeline | 5-8% | - Prepare and deploy models for operational use - Automate, monitor, and maintain the data science pipeline |
| Performing Exploratory Data Analysis | 25-36% | - Apply descriptive statistics and data visualization techniques - Identify patterns, anomalies, missing values, and data quality issues - Explore distributions, relationships, and statistical properties |
