Calendar – Data Quality Academy

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Production Testing

Model Monitoring (Drift, Performance, Latency)
A/B Testing and Canary Deployment
Alerting, Rollback, and Model Governance
Model Testing in the CI/CD Pipeline

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Model Behavior Testing

Test Cases and Test Sets
Adversarial Testing
Model Testing Across Different User Segments (Fairness Testing)
Explainability and Interpretability (SHAP, LIME)

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Model Evaluation and Validation

Key Metrics (Accuracy, Precision, Recall, F1 Score, ROC, MAE, RMSE…)
Cross-Validation Strategies
Overfitting and underfitting

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Testing of Training Data

Outlier and Anomaly Detection
Class Balance Analysis
Bias Detection and Distribution Issues

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Introduction to AI/ML Testing

How Traditional Software Testing Differs from AI Model Testing
Model Lifecycle: Data → Training → Validation → Deployment
Where QA Plays the Most Critical Role

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