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Learn Linear Regression online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Sungkyunkwan University
In this course, you will: a) understand the basic concepts of machine learning. b) understand a typical memory-based method, the K nearest neighbor method. c) understand linear regression. d) understand model analysis. Please make sure that you’re comfortable programming in Python and have a basic…
Illinois Tech
This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven such as finance, retain, tech, healthcare, government and many more. The opportunity is endless. This…
Howard University
In this course, you'll learn how to distinguish between the different types of regression models. You will apply the Method of Least Squares to a dataset by hand and using Python. In addition, you will learn how to employ a linear regression model to identify scenarios. Let's get started!
National Taiwan University
本課程為三模組系列課程之第三模組。 此系列課程專門教授各種線性迴歸形式 (regression-type) 的統計分析模型與技術。此系列課程以大量多樣之商管實務案例進行解說，並以 R 統計語言進行建模分析，提供完整的命令稿 (script) 與資料集讓同學們實地操作演練，培養統計分析思維與實戰技能。 本第三模組為高階課程，著重於二元資料 (binary data) 與計數資料 (counted data) 的建模策略與應用，從二元反應變數的基本分析，到 GLM 架構下的邏輯斯迴歸 (Logistic Regression) 與對數線性迴歸 (Log-Linear Regression)，涵蓋…
EDUCBA
Master the fundamentals and practical applications of linear regression while building predictive models using SPSS and Excel. In this hands-on course, you will learn how to construct regression models, interpret statistical outputs, evaluate statistical significance, and apply predictive analytics…
Coursera
In this 2-hour long project-based course, you will learn how to implement Linear Regression using Python and Numpy. Linear Regression is an important, fundamental concept if you want break into Machine Learning and Deep Learning. Even though popular machine learning frameworks have implementations…
Coursera
This course is your entry point into the world of predictive analytics with R. Designed for aspiring data analysts and business professionals, this course empowers you to build and interpret multiple linear regression models from the ground up. You will move beyond simply running code and learn to…
Coursera
In this 1 hour long project-based course, you will learn to build a linear regression model using Pyspark ML to predict students' admission at the university. We will use the graduate admission 2 data set from Kaggle. Our goal is to use a Simple Linear Regression Machine Learning Algorithm from the…
Coursera
In this 1.5-hour long project-based course, you will be able to: - Understand the theory and intuition behind Simple and Multiple Linear Regression. - Import Key python libraries, datasets and perform data visualization - Perform exploratory data analysis and standardize the training and testing da…
Coursera
Hello everyone and welcome to this hands-on guided project on simple linear regression for the absolute beginner. In simple linear regression, we predict the value of one variable Y based on another variable X. X is called the independent variable and Y is called the dependent variable. This guided…
Coursera
Welcome to this project-based course Building Statistical Models in R: Linear Regression. This is a hands-on project that introduces beginners to the world of statistical modeling. In this project, you will learn the basics of building statistical models in R. We will start this hands-on project by…
Simplilearn
This foundational course on linear regression equips you with the essential knowledge and hands-on skills to build predictive models. Begin with core ML concepts and algorithms, then progress to simple and multiple linear regression techniques. Learn how regression is applied in real-world scenario…
Coursera
Learn how to make your regression models trustworthy, not just accurate. In this short, hands-on course, you'll explore the key assumptions behind classical linear regression and practice verifying them in RStudio. You'll fit an Ordinary Least Squares (OLS) model, visualize residuals, and detect pa…
EDUCBA
Build practical skills in linear regression, Python, and supervised machine learning through a structured, project-driven course. Designed for beginners and aspiring data professionals, this course guides you through the complete regression workflow—from identifying a machine learning use case and…
EDUCBA
This course provides comprehensive training in regression analysis and forecasting techniques for data science, emphasizing Python programming. You will master time-series analysis, forecasting, linear regression, and data preprocessing, enabling you to make data-driven decisions across industries.…
Corporate Finance Institute
Linear regression analysis is critical for understanding and defining the strength of the relationship between variables. This analysis can be used to make predictions for a variable given the value of another known variable. This course provides an overview of linear regression. You will learn how…
EDUCBA
Build practical machine learning and deep learning skills with TensorFlow through a structured path from data preparation to neural network development. You’ll begin by transforming raw data through feature encoding, custom preprocessing, and feature engineering, then apply linear regression techni…
EDUCBA
Build a strong foundation in Linear Regression with R and learn how to develop, evaluate, and optimize predictive models for data-driven decision-making. This course takes you through a structured learning journey, beginning with the fundamentals of regression concepts and progressing to advanced r…
EDUCBA
Master the complete workflow of house price prediction with linear regression in Python through a practical, project-based learning experience. In this course, you will learn how to prepare housing datasets, apply data preprocessing and transformation techniques, engineer meaningful features, perfo…
EDUCBA
Build Web Apps, ML Models & Encrypt Data
