Ridge Regression Courses and Certifications

NPTEL-NOC IITM

Handling Multicollinearity with Ridge Regression in Python

Implement Ridge Regression using Python and sklearn to handle multicollinearity in data analysis.

• YouTube
• 18 minutes
• On-Demand
• Free Video

Data Science Conference

Introduction to Lasso and Ridge Regression Models in R

Master linear regression regularization techniques through Lasso and Ridge methods in R, focusing on preventing overfitting and improving model reliability for more accurate predictions and estimations.

• YouTube
• 2 hours 10 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

Regularization Part 1 - Ridge (L2) Regression

Learn Ridge Regression to prevent overfitting, solve unsolvable equations, and optimize models. Covers main ideas, details, applications for various data types and models, and usage with limited data.

• YouTube
• 20 minutes
• On-Demand
• Free Video

UofU Data Science

Feature Selection - Linear Regression, Ridge Regression, and Lasso - L19

Master feature selection techniques in linear regression, including Ridge and Lasso methods, while understanding sparsity, normalization, and the complexities of interpreting coefficients.

• YouTube
• 1 hour 23 minutes
• On-Demand
• Free Video

Diving Deep into Regression

Master advanced regression techniques from polynomial to elastic net, with hands-on practice using real datasets for predictive modeling and performance optimization.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Regression Models for Prediction

Master regression modeling techniques to build predictive models using Python, covering multiple linear, polynomial, lasso and ridge regression, along with essential model evaluation metrics and visualization methods.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Model Evaluation and Optimization

Master advanced techniques for evaluating and optimizing regression models, from cross-validation to hyperparameter tuning and regularization methods for enhanced predictive accuracy.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

PredictHealth's Advanced Pricing System

Master advanced modeling techniques to build state-of-the-art insurance pricing systems with non-linear patterns, feature interactions, regularization, and robust validation methods.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

The Supervised Machine Learning Bootcamp

1418 ratings at Udemy

Data Science, Python, sk learn, Decision Trees, Random Forests, KNNs, Ridge Lasso Regression, SVMs

• Udemy
• 5 hours 49 minutes
• On-Demand
• Paid Course

Supervised Machine Learning: Regression

828 ratings at Coursera

Explore supervised machine learning regression techniques, from linear models to regularization methods, with hands-on practice in error metrics, data splitting, and model selection for continuous outcome prediction.

• Coursera
• 20 hours 28 minutes
• On-Demand
• Paid Course

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
• On-Demand
• Free Video

Resampling, Selection and Splines

Explore advanced statistical learning techniques for data science, including resampling methods, model optimization, and non-linear approaches to enhance prediction accuracy and interpretability.

• Coursera
• 15 hours 56 minutes
• On-Demand
• Paid Course

Machine Learning and Data Analytics Part 2

Explore advanced data mining techniques including clustering, neural networks, SVMs, and text mining with real-world applications across engineering sectors.

• Coursera
• 18 hours 7 minutes
• On-Demand
• Paid Course

Machine Learning: Regression

This course covers key supervised machine learning topics in regression analysis. You’ll learn to train and test regression models. Ideal for aspiring data scientists and machine learning engineers.

• edX
• 2 weeks, 20-24 hours a week
• On-Demand
• Free Online Course (Audit)

AnalystPrep

Machine Learning and Prediction - Part A - FRM Part 1 2025

Master regression techniques and regularization methods for predictive modeling in FRM, covering linear and logistic approaches, categorical variable encoding, and ridge versus LASSO methods.

• YouTube
• 31 minutes
• On-Demand
• Free Video