Linear Models Courses and Certifications

Introduction to Supervised Machine Learning

Implement linear and logistic regression from scratch with gradient descent on the Wine Quality dataset, then evaluate models with regression metrics and correlation heatmaps.

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

Industrial Optimization: Models & Linear Programming

Formulate and solve linear programs for industrial operations: build LP models graphically and in LINGO, apply the simplex method, and transform non-standard forms.

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

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

Machine Learning with Python: from Linear Models to Deep Learning

Implement and analyze linear models, kernel machines, neural networks, and graphical models in Python, tackling classification, regression, clustering, and reinforcement learning projects end to end.

• MITx Online
• Self-Paced
• Free Online 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

Career Certificate

Practical Machine Learning: Foundations to Neural Networks

5 ratings at Coursera

Formulate learning tasks with probability and statistics, weigh Bayesian against frequentist views, fit parameters by maximum likelihood, build linear regression and classification models, and design neural networks.

• Coursera
• 12 weeks, 8 hours a week
• Self-Paced
• Paid Course
• 3 courses

R Programming 101

Multiple Regression Analysis - From Simple Linear to Complex Models

Master multiple regression analysis in R, covering variable selection, confounding, collinearity, outliers, interactions, and assumption validation for robust statistical modeling.

• YouTube
• 2 hours 19 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Instrumental Variable Estimation for Multiple Linear Regression Models - Part IV

Explore IV techniques for MLRM, generalized MLRM, multiple instruments, and endogenous variables in econometric modeling.

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

Pascal Poupart

Logistic Regression and Generalized Linear Models

Learn logistic regression and generalized linear models through the exponential family, Newton's method, classification, app recommendation, and sparsity.

• YouTube
• 1 hour 35 minutes
• Self-Paced
• Free Video

JuliaHub

Linear ARX Models in System Identification with Julia - Part 2

Master linear ARX modeling in Julia through hands-on exploration of system identification techniques, from basic concepts to practical implementation using least-squares estimation and uncertainty quantification.

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

Linear Rates, Products, and Models - Lecture 7

Explore linear interest rate products, market structure, valuation methods, and the transition from LIBOR to SOFR in financial markets with MIT's quantitative finance expert.

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

NPTEL-NOC IITM

Generalised Linear Models: Introduction to Natural Exponential Family and Binomial Distributions

Explore Generalised Linear Models and Natural Exponential Family, focusing on Binomial Distributions and their applications in statistical modeling.

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

UofU Data Science

Generalized Linear Models and Linear Regression - Lecture 11

Dive into advanced statistical concepts including generalized linear models, nonlinear basis functions, and regularization techniques for robust data analysis and point estimation.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Dyalog User Meetings

Taming Regression Using APL - From Basic Linear Models to Advanced Applications

Master statistical regression techniques using APL through practical examples, from basic linear models to advanced non-linear and logistic regression, with hands-on demonstrations using TamStat software.

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

JuliaHub

System Identification with Julia: Prediction-Error Method for Linear Models - Part 4

Master linear state-space modeling through prediction-error method (PEM) in Julia. Implement parameter estimation for linear ODEs, validate results, and explore advanced PEM options for system identification.

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