Certificate in AI Measurement for Data Professionals
-- ViewingNowThe Certificate in AI Measurement for Data Professionals is a comprehensive course designed to equip learners with the essential skills needed to excel in the rapidly evolving AI industry. This course focuses on the importance of AI measurement, a critical aspect of AI development that is often overlooked.
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โข Fundamentals of AI Measurement: Introduction to AI measurement concepts, metrics, and evaluation techniques.
โข Data Preparation for AI Measurement: Data preprocessing, cleaning, and transformation techniques for AI measurement.
โข Performance Metrics for Supervised Learning: Accuracy, precision, recall, F1-score, ROC curve, AUC, and other metrics for supervised learning algorithms.
โข Performance Metrics for Unsupervised Learning: Cluster validity indices, silhouette score, elbow method, and other metrics for unsupervised learning algorithms.
โข Evaluation Strategies for AI ModelsCross-validation, bootstrapping, holdout, and other evaluation strategies for AI models.
โข AI Measurement Tools and Libraries: Introduction to popular AI measurement tools and libraries, such as scikit-learn, TensorFlow, and PyTorch.
โข Ethical Considerations in AI Measurement: Addressing fairness, accountability, transparency, and explainability in AI measurement.
โข AI Measurement Best Practices: Guidelines and best practices for effective AI measurement in data professional settings.
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