Coursera MOOC / Non-credit 0

Supervised machine learning and performance evaluation

Name: Supervised machine learning and performance evaluation
Price: 49 USD
Availability: InStock

About this course

This course is designed for data scientists, machine learning practitioners, and graduate students who want to understand how to evaluate and select models reliably in real-world applications. It is particularly relevant for learners working with predictive models who need to ensure their results generalise beyond the training data. You’ll learn the statistical foundations behind performance estimation and gain hands-on experience with essential techniques such as cross-validation, model selection, and nested resampling. By the end of the course, you’ll be equipped to design robust evaluation workflows and make confident, evidence-based modeling decisions.

67/100

CourseAsk score

What the provider tells you: 31/45
Who stands behind it: 20/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

understand the statistical foundations of performance estimation
apply cross-validation techniques
perform model selection and nested resampling
design evaluation workflows for predictive models

Course objectives

equip learners with the skills to evaluate models in real-world scenarios
enhance understanding of model generalization
develop hands-on experience with performance evaluation techniques

Machine Learning #machine learning #model evaluation #predictive modeling #data science #cross-validation #model selection #statistical foundations #resampling techniques #performance estimation

$49.00

Price shown by Coursera — confirm on their site.

Enroll on Coursera

You'll be redirected to Coursera to complete enrollment.