Cross-Validation Courses and Certifications

PredictHealth's Multi-Factor Cost Models

Develop multi-factor insurance cost models by combining categorical variables, robust preprocessing, cross-validation, and custom feature engineering.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

PredictHealth's Advanced Pricing System

Build an insurance pricing prediction system using polynomial features, interaction terms, regularization, tuning, and robust cross-validation.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Apprenez à évaluer et comparer des modèles supervisés par validation croisée pour éviter le sur-apprentissage.

• OpenClassrooms
• Self-Paced
• Free Certificate

Supervised Machine Learning: Regression

846 ratings at Coursera

Train linear and polynomial regression models to predict continuous outcomes, compare them with error metrics, and apply cross validation plus Ridge, LASSO, and elastic net regularization.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

Data Science: Building Machine Learning Models

120 ratings at edX

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

• edX
• 8 weeks, 2-4 hours a week
• Self-Paced
• Free Online Course (Audit)

Statistical Learning with Python

Master statistical learning fundamentals through hands-on Python implementation, covering regression, classification, neural networks, and unsupervised methods without heavy mathematics.

• YouTube
• 20 hours 18 minutes
• Self-Paced
• Free Video

Statistical Learning with R

Master supervised and unsupervised learning techniques using R, from linear regression to deep learning, with hands-on implementation of modern data science methods.

• YouTube
• 20 hours 28 minutes
• Self-Paced
• Free Video

Coursera

Classification Trees in Python, From Start To Finish

233 ratings at Coursera

Build a classification tree in Python with scikit-learn: handle missing data, one-hot encode categorical features, and apply cost complexity pruning and cross validation to predict heart disease.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Regression Analysis

10 ratings at Coursera

Learn regression as supervised learning: fit linear and polynomial models, apply Ridge, Lasso and Elastic Net, run cross-validation, and combine models with bagging, boosting and stacking.

• Coursera
• 6 weeks, 7 hours a week
• Self-Paced
• Paid Course

Resampling, Selection and Splines

Apply generalized least squares, ridge regression, LASSO, and PCA, and use k-fold cross-validation and bootstrapping to evaluate models and quantify uncertainty.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Foundations of Statistical Learning & Algorithms

Build the mathematical groundwork of statistical learning: solve linear systems, apply eigenvalues, Cholesky and singular value decomposition, reason with Bayes' theorem, and validate models via cross-validation.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course

Coursera

Optimize AI: Build & Evaluate Predictive Models

Build and evaluate predictive models with scikit-learn: train logistic-regression and clustering models, apply 5-fold cross-validation, and refine features against accuracy and F1 targets.

• Coursera
• 1 hour 59 minutes
• Self-Paced
• Paid Course

Coursera

Building, Optimizing, and Validating Machine Learning Models

Train and compare models with ML APIs, tune hyperparameters, validate with k-fold and stratified sampling, explain results with SHAP, and automate end-to-end ML pipelines.

• Coursera
• 9 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Statistical Thinking & Predictive Modeling

Move from exploratory analysis to deployed models: run t-tests and confidence intervals, build cross-validated random forests, handle class imbalance with SMOTE, and predict customer lifetime value.

• Coursera
• 11 weeks, 1 hour a week
• Self-Paced
• Paid Course

EDUCBA

Python: Implement & Evaluate Random Forests for ML

Build and evaluate Random Forest classifiers in Python: prepare the SONAR dataset, construct decision trees with the Gini index, and validate classification performance with cross-validation.

• Coursera
• 3 hours 7 minutes
• Self-Paced
• Paid Course