Regression Models Courses and Certifications

Building Regression Models with Linear Algebra

Learn to distinguish types of regression models and apply the Method of Least Squares by hand and in Python, then interpret linear regression models on real examples.

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

Model Evaluation and Optimization

Hands-on Python practice pushing regression models further: advanced error metrics, K-fold cross-validation on housing data, GridSearchCV tuning, and Ridge/Lasso regularization.

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

Career Certificate

Implementing AI Algorithms from Scratch in C++ (Part 1)

Implement core machine learning algorithms from scratch in C++, including regression, classification, and gradient-descent optimization.

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

Coursera

Regression: Identify Assumptions & Apply Models

Fit an OLS model in RStudio, test the classical linear regression assumptions, visualize residuals, detect heteroscedasticity, and communicate diagnostic findings clearly.

• Coursera
• 2 hours 1 minute
• Self-Paced
• Paid Course

EDUCBA

Regression & Logistic Models in Excel & Minitab

Apply advanced regression and logistic regression in Excel and Minitab: interpret coefficients, diagnose multicollinearity, read odds ratios, and run t-tests, ANOVA, and correlation.

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

Coursera

Predict and Validate Regression Models in R

Build and interpret multiple linear regression models in R, diagnose assumptions with residual plots, and test stability with k-fold cross-validation.

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

EDUCBA

Logistic Regression with SAS: Build & Evaluate Models

Build logistic regression models in SAS with PROC LOGISTIC: handle missing values, encode categoricals, cluster and select predictors, and evaluate with confusion matrices and logit plots.

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

EDUCBA

Analyze Advanced Data Using Minitab Regression Models

Build linear, logistic, multinomial, and CART models in Minitab: read regression outputs, compare models with scatter plots and diagnostics, and interpret decision trees.

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

EDUCBA

Analyze Real Estate Valuation and Regression Models

Integrates ethical judgment with real estate valuation and regression analysis to support disciplined investment decisions and assess model limitations.

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

Linear Regression and Linear Models

Learn how linear regression and linear models use continuous and categorical values to predict a continuous outcome, with least squares, multiple regression, and R examples.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

Advanced Methods in Machine Learning Applications

Apply ensemble methods, regression, clustering, and reinforcement learning by building random forests, coding logistic regression from scratch, running k-means and DBSCAN, and implementing Q-learning.

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

Application of Forecasting, Regression and Time Series Models

Apply forecasting, regression, and time-series models to produce accurate, mathematically grounded forecasts for rational decisions.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

MGH Institute of Health Professions

Regression Models in Healthcare

In this course, you will begin learning about more advanced multivariate statistical methods that are regularly used in healthcare data analysis and practice applying them to healthcare data in the st

• edX
• 4 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