Certificate in Model Evaluation & Performance Metrics
-- viewing nowThe Certificate in Model Evaluation & Performance Metrics course is a powerful program designed to equip learners with essential skills in model evaluation and performance analysis. In today's data-driven world, these skills are in high demand across industries, as organizations seek to make informed decisions based on accurate and reliable models.
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Course Details
• Model Evaluation Metrics Overview
• Regression Metrics: Mean Absolute Error, Mean Squared Error, R-squared
• Classification Metrics: Accuracy, Precision, Recall, F1 Score
• ROC Curve and AUC: Concept and Importance
• Cross-validation Techniques: K-fold Cross-Validation, Stratified K-fold Cross-Validation
• Confusion Matrix: Components and Analysis
• Performance Metrics for Imbalanced Datasets: Precision-Recall Curve, Specificity
• Model Selection Criteria: Bias-Variance Tradeoff, Overfitting and Underfitting
• Evaluation Dashboards and Visualization Tools
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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