Executive Development Programme in AI Metrics: High-Performance Techniques
-- ViewingNowThe Executive Development Programme in AI Metrics: High-Performance Techniques certificate course is a comprehensive program designed to empower professionals with the essential skills needed to thrive in the rapidly evolving AI landscape. This course highlights the importance of AI metrics in driving high-performance techniques and decision-making for businesses.
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⢠Introduction to AI Metrics: Understanding the basics of AI metrics, their importance, and how they are used in the industry.
⢠Data Preparation for AI Metrics: Techniques for data cleaning, preprocessing, and feature engineering to ensure accurate AI metric calculations.
⢠Performance Metrics in AI: Exploring various performance metrics in AI, including accuracy, precision, recall, F1 score, ROC curve, AUC, and log loss.
⢠Regression Metrics in AI: Diving into regression-specific AI metrics, such as R-squared, mean squared error, mean absolute error, and adjusted R-squared.
⢠Classification Metrics in AI: Learning about classification-specific AI metrics, such as confusion matrix, sensitivity, specificity, positive predictive value, and negative predictive value.
⢠Evaluating Model Performance with AI Metrics: Techniques for evaluating AI model performance using various metrics and selecting the best model based on the evaluation.
⢠Interpreting AI Metrics for Business Decisions: Understanding how to interpret AI metrics in a business context and make informed decisions based on the results.
⢠Best Practices in AI Metrics: Learning about industry best practices in AI metrics, including data privacy, security, and ethical considerations.
⢠Advanced AI Metrics Techniques: Exploring advanced AI metric techniques, such as explainability, interpretability, and uncertainty quantification.
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