Linear Regression Courses and Certifications

EDUCBA

Linear Regression with R: Build & Optimize

Master linear regression fundamentals and advanced techniques in R, building simple to multiple models, applying dummy variables, and optimizing through backward elimination for real-world data analysis.

• Coursera
• 6 hours 33 minutes
• Self-Paced
• Paid Course

Great Learning

Linear Regression in Machine Learning - Machine Learning Tutorial

Comprehensive exploration of linear regression in machine learning, covering key concepts, applications, and implementation in Python. Ideal for beginners seeking practical understanding of predictive modeling.

• YouTube
• 2 hours 15 minutes
• Self-Paced
• Free Video

Python for Linear Regression in Machine Learning

335 ratings at Udemy

Linear and Non-Linear Regression, Lasso Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection | Outliers Removal

• Udemy
• 14 hours 36 minutes
• Self-Paced
• Paid Course

NPTEL-NOC IITM

Diagnostics to Improve Linear Model Fit - OLS Analysis and Residual Plots

Explore techniques to enhance linear model fit through residual analysis, normality checks, and outlier detection in OLS regression.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Simons Institute

Benign Overfitting in Linear Prediction

Explore the phenomenon of benign overfitting in linear prediction, its implications for deep learning, and its impact on adversarial examples in machine learning.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Artem Kirsanov

What Textbooks Don't Tell You About Curve Fitting

Discover the probabilistic interpretation behind linear regression, exploring how least squares objectives arise from maximizing data probability and how different priors lead to various regularization techniques.

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

DeepLearning.AI;  Stanford

Supervised Machine Learning: Regression and Classification

32507 ratings at Coursera

Develop machine learning skills using Python, covering regression and classification techniques with hands-on practice in NumPy and scikit-learn for real-world AI applications.

• Coursera
• 1 day 9 hours 19 minutes
• Self-Paced
• Paid Course

Career Certificate

Business Statistics and Analysis

12721 ratings at Coursera

Equip yourself with essential business data analysis tools, from spreadsheet functions to data modeling, probability concepts, and linear regression, culminating in a practical capstone project.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Regression Analysis - Ordinary Least Squares Estimation and Statistical Properties - Lecture 8

Dive into advanced linear regression concepts including OLS estimation, Hat matrix projections, statistical inference with t- and F-tests, and model diagnostics for finance applications.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

UofU Data Science

Machine Learning: Least Mean Square Regression - Lecture 12

Dive into advanced linear regression concepts, exploring overfitting, gradient descent, and practical plotting techniques for enhanced machine learning understanding.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

UofU Data Science

Least Mean Square Regression for Machine Learning - Lecture 11

Dive into least mean square regression, exploring loss function minimization and gradient descent methods for effective linear regression implementation and optimization.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Regression Series

Comprehensive exploration of regression analysis, covering key concepts, advanced techniques, and model assumptions for data-driven decision-making.

• YouTube
• 4 hours 30 minutes
• Self-Paced
• Free Video

statisticsmatt

Generalized Linear Models

Comprehensive exploration of Generalized Linear Models, covering various regression techniques including Probit, Logistic, Complementary Log-Log, Poisson, Ordinal Logistic, and Multinomial Logistic.

• YouTube
• 3 hours 30 minutes
• Self-Paced
• Free Video

statisticsmatt

General Linear Models - Background Material

Comprehensive exploration of statistical concepts and matrix algebra, covering distributions, quadratic forms, projection matrices, and advanced matrix operations for linear modeling.

• YouTube
• 4 hours 30 minutes
• Self-Paced
• Free Video

statisticsmatt

General Linear Models - Design of Experiments

Comprehensive exploration of general linear models and experimental design, covering ANOVA, factorial designs, and advanced statistical concepts with practical examples and R software illustrations.

• YouTube
• 22 hours
• Self-Paced
• Free Video