Logistic Regression Courses and Certifications

Credit Risk Modeling in Python

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

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

Statistics Fundamentals in R

Discover the power of statistics in R. Learn the key statistical concepts, topics, and techniques used by data scientists and statisticians every day.

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

Introduction to Predictive Analytics in Python

In this course you'll learn to use and present logistic regression models for making predictions.

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

Generalized Linear Models in R

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

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

Introduction to Spark SQL in Python

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

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

Machine Learning for Marketing in Python

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

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

Generalized Linear Models in Python

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

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

Supervised Machine Learning in Python

Master the most popular supervised machine learning techniques to begin making predictions with labeled data.

• DataCamp
• 1 day 1 hour
• Self-Paced
• Free Trial Available

HR Analytics: Predicting Employee Churn in R

Predict employee turnover and design retention strategies.

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

Supervised Machine Learning in R

Generate, explore, evaluate, and tune the parameters of different supervised machine learning models.

• DataCamp
• 1 day 1 hour
• Self-Paced
• Free Trial Available

Python Data Science & Machine Learning Program NYC (High School & College)

Master Python programming, data science, and machine learning fundamentals through hands-on projects. From basic syntax to advanced regression analysis, build practical skills in data visualization and predictive modeling.

• Noble Desktop
• 45 hours
• Self-Paced
• $2,195.00

Introduction to Machine Learning

3822 ratings at Coursera

Foundational understanding of machine learning models, hands-on implementation with PyTorch, and applications across industries from medical diagnostics to image recognition and text prediction.

• Coursera
• 1 day 1 hour 47 minutes
• Self-Paced
• Paid Course

Coursera

Logistic Regression with NumPy and Python

396 ratings at Coursera

Implement logistic regression from scratch using NumPy and Python. Gain deep understanding of machine learning fundamentals through hands-on coding of gradient descent, cost function, and model building.

• Coursera
• 1 hour 35 minutes
• Self-Paced
• Paid Course

Julia Silge

Fit and Predict With Logistic Regression for Bird Bath Observations in Australia

Learn to model bird bath observations in Australia using tidymodels, combining model specifications with feature engineering recipes for effective fitting and prediction.

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

Great Learning

Linear Regression vs Logistic Regression - Learn Data Science

This video teaches Linear Regression, Logistic Regression and the key differences between both with a variety of demonstrations & examples to help you get started on the right foot.

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