Simple Linear Regression Courses and Certifications

Regression and Classification

13 ratings at Coursera

Explore statistical modeling concepts, including regression, classification, and unsupervised techniques. Learn when to use specific models, how to tune them, and understand trade-offs for informed decision-making.

• Coursera
• 1 day 10 hours 49 minutes
• On-Demand
• Free Online Course (Audit)

Regression Modeling for Marketers

Elevate marketing skills with regression analysis, data visualization, and advanced statistical techniques for quantifying, explaining, and predicting marketing outcomes and consumer behavior.

• Coursera
• 19 hours 9 minutes
• On-Demand
• Free Online Course (Audit)

Correlation and Regression in R

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

R, ggplot, and Simple Linear Regression

3792 ratings at Udemy

Begin to use R and ggplot while learning the basics of linear regression

• Udemy
• 2 hours 14 minutes
• On-Demand
• Free Online Course

All-in-One:Machine Learning,DL,NLP,AWS Deply [Hindi][Python]

386 ratings at Udemy

Complete hands-on Machine Learning Course with Data Science, NLP, Deep Learning and Artificial Intelligence

• Udemy
• 17 hours 43 minutes
• On-Demand
• Paid Course

Machine Learning Fundamentals [Python]

146 ratings at Udemy

Understanding Machine Learning for Data Science in python. Best skill to get in free time.

• Udemy
• 1 hour
• On-Demand
• Free Online Course

Mastering Machine Learning: Course-1

115 ratings at Udemy

Learn key machine learning concepts including supervised and unsupervised learning, regression, and classification, with hands-on implementation of simple linear regression in Python.

• Udemy
• 1-2 hours
• On-Demand
• Free Online Course

Linear Regression

15 ratings at Coursera

Learn to apply linear regression techniques using R, covering simple and multiple regression, qualitative predictors, and statistical inference for data-driven career applications.

• Coursera
• 1 day 3 hours 3 minutes
• On-Demand
• Free Online Course (Audit)

Statistics for Business Analytics: Modelling and Forecasting

Learn to apply statistical techniques for business analytics, covering correlation, regression, and time series forecasting to predict future trends and make data-driven decisions.

• edX
• 10 weeks, 4-8 hours a week
• On-Demand
• Free Online Course (Audit)

IISER Pune;  NPTEL

Regression Analysis

Learn powerful regression analysis techniques for predicting future outcomes. Master simple and multiple linear regression, model assumptions, dummy variables, polynomial regression, and generalized linear models.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Explore fitting and interpreting linear regression with a single predictor variable using Python, focusing on model creation, interpretation, and effective communication of findings.

• Codecademy
• 2 hours
• On-Demand
• Free Trial Available

Great Learning

Linear Regression in Python - Machine Learning - Linear Regression Algorithm

Comprehensive tutorial on linear regression, covering simple and multiple regression with Excel and Python implementations. Includes step-by-step examples and practical applications in data analysis.

• YouTube
• 2 hours 3 minutes
• On-Demand
• Free Video

Machine Learning

Explore machine learning models through hands-on tutorials in Python and Julia, covering clustering, regression, neural networks, and more. Practical examples with code provided.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

The AI University

Machine Learning Using Spark MLLib

Learn to implement machine learning algorithms using Spark MLLib, covering linear regression techniques, data preprocessing, model building, and evaluation methods in a hands-on, practical approach.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Video

jbstatistics

Simple Linear Regression

Learn to analyze relationships between variables using linear regression, covering model interpretation, assumptions, inference, and practical applications.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video