Logistic Regression Courses and Certifications

Supervised Machine Learning: Classification

459 ratings at Coursera

Learn to train and evaluate classification models, including logistic regression, decision trees, and ensembles. Gain hands-on experience with best practices like handling unbalanced classes and using various error metrics.

• Coursera
• 1 day 17 minutes
• Self-Paced
• Paid Course

Credit Risk Modeling in Python

7910 ratings at Udemy

A complete data science case study: preprocessing, modeling, model validation and maintenance in Python

• Udemy
• 6 hours 52 minutes
• Self-Paced
• Paid Course

[2026] Machine Learning: Natural Language Processing (V2)

7223 ratings at Udemy

NLP: Use Markov Models, NLTK, Agentic AI, Artificial Intelligence, Machine Learning, and Data Science in Python

• Udemy
• 23 hours 31 minutes
• Self-Paced
• Paid Course

Python Machine Learning Immersive (Live Online)

330 ratings at CourseHorse

Master the essential skills to excel in the booming field of machine learning, including regression and classification algorithms, feature selection, and model evaluation.

• CourseHorse
• Self-Paced
• $1,895.00

Classification and Planned Experiments

Master classification techniques like K-nearest neighbor and logistic regression, plus experimental design principles for causal analysis using R and Python.

• Coursera
• 5 hours 47 minutes
• Self-Paced
• Paid Course

Machine Learning Practical: 6 Real-World Applications

3232 ratings at Udemy

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python

• Udemy
• 8 hours 37 minutes
• Self-Paced
• Paid Course

Complete Machine Learning with R Studio - ML for 2026

2725 ratings at Udemy

Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language - R studio

• Udemy
• 12 hours 3 minutes
• Self-Paced
• Paid Course

Credential

SAS Statistical Business Analyst

228 ratings at Coursera

Enhance predictive and statistical modeling skills to drive data-informed business outcomes. Learn hypothesis testing, regression modeling, and logistic regression using SAS software.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Machine Learning: Supervised Learning

25 ratings at Coursera

Explore supervised ML algorithms, prediction tasks, and model selection. Learn to improve performance using linear/logistic regression, KNN, decision trees, ensembling methods, and kernel techniques like SVM.

• Coursera
• 22 hours 48 minutes
• Self-Paced
• Paid Course

Fundamentals of Natural Language Processing

17 ratings at Coursera

Explore the foundations of NLP through probabilistic language models, neural networks, and vector-based meaning representations, learning to implement N-gram models, text classifiers, and word embeddings.

• Coursera
• 1 day 6 minutes
• Self-Paced
• Paid Course

Classification Analysis

Explore key classification algorithms, their applications, and evaluation methods. Gain hands-on experience through tutorials and case studies to solve real-world data analysis problems.

• Coursera
• 1 day 14 hours 14 minutes
• Self-Paced
• Paid Course

Modeling Climate Anomalies with Statistical Analysis

Learn to model climate data using statistical analysis in Python, covering data visualization, predictive modeling, and regression techniques with emphasis on practical application to climate datasets.

• Coursera
• 7 hours 21 minutes
• Self-Paced
• Paid Course

Marketing Analytics Capstone Project

30 ratings at Coursera

Apply marketing analytics skills to conduct exploratory data analysis, examine variable relationships, and develop a predictive model for solving real-world marketing problems.

• Coursera
• 11 hours 1 minute
• Self-Paced
• Paid Course

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
• Self-Paced
• Paid Course

Introduction to Statistical Analysis: Hypothesis Testing

175 ratings at Coursera

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.

• Coursera
• 10 hours 17 minutes
• Self-Paced
• Paid Course