Linear Regression Courses and Certifications

Inference for Linear Regression in R

176 ratings at DataCamp

Previously, you learned the fundamentals of both statistical inference and linear models; now, the next step is to put them together.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Linear Regression and Modeling

1793 ratings at Coursera

Fit, examine, and interpret simple and multiple linear regression models in R and RStudio, covering outliers, inference, variability partitioning, model selection, and diagnostics.

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

Linear Regression for Business Statistics

1370 ratings at Coursera

Build and interpret linear regression models in Excel, applying dummy variables, multicollinearity checks, mean centering, interaction effects, and log-log and semi-log transformations.

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

Linear Regression Modeling for Health Data

Fit and interpret regression models for health data: move from the t-test to simple linear regression, then adjust for multiple predictors with a continuous outcome.

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

Linear Regression in R for Public Health

533 ratings at Coursera

Build linear regression models in R using COPD data: generate Pearson and Spearman correlations, add categorical predictors and interaction terms, and test model assumptions.

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

Data Science: Linear Regression

29 ratings at edX

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

• edX
• 8 weeks, 1-2 hours a week
• Self-Paced
• Free Online Course (Audit)

Coursera

Linear Regression with Python

442 ratings at Coursera

Implement linear regression from scratch with Python and NumPy, coding gradient descent to see how the optimization algorithm and training process actually work.

• Coursera
• 1 hour 45 minutes
• Self-Paced
• Paid Course

Deep Learning Prerequisites: Linear Regression in Python

6815 ratings at Udemy

Data science, machine learning, and artificial intelligence in Python for students and professionals

• Udemy
• 6 hours 21 minutes
• Self-Paced
• Paid Course

Complete Linear Regression Analysis in Python

1567 ratings at Udemy

Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also

• Udemy
• 7 hours 35 minutes
• Self-Paced
• Paid Course

Deep Learning Foundation : Linear Regression and Statistics

1406 ratings at Udemy

Learn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine Learning

• Udemy
• 6 hours 45 minutes
• Self-Paced
• Paid Course

Coursera

Simple Linear Regression for the Absolute Beginner

68 ratings at Coursera

Predict the value of one variable from another: build a simple linear regression model with independent and dependent variables in a hands-on portfolio project.

• Coursera
• 2 hours 4 minutes
• Self-Paced
• Paid Course

Excel Analytics: Linear Regression Analysis in MS Excel

1235 ratings at Udemy

Linear Regression analysis in Excel. Analytics in Excel includes regression analysis, Goal seek and What-if analysis

• Udemy
• 4 hours 3 minutes
• Self-Paced
• Paid Course

Linear Regression

31 ratings at Coursera

Fit simple and multiple linear regression models in R, derive least squares estimators with matrices, handle qualitative predictors, and draw inferences and predictions.

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

Coursera

Building Statistical Models in R: Linear Regression

20 ratings at Coursera

Build and interpret simple and multiple linear regression models in R, exploring data with visualizations and checking model assumptions using diagnostic plots.

• Coursera
• 2 hours 20 minutes
• Self-Paced
• Paid Course

EDUCBA

Linear Regression & Predictive Modeling with SPSS

16 ratings at Coursera

Build linear regression models in SPSS and Excel: read scatter plots and T-values, interpret coefficients, validate models on new data, and forecast debt-to-income and credit risk.

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