Classification Algorithms Courses and Certifications

Classification Algorithms and Metrics

Implement classification algorithms from scratch in Python: logistic regression, k-nearest neighbors, Naive Bayes and decision trees, plus confusion matrix, precision, recall and AUC-ROC metrics.

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

Classification Algorithms and Metrics

Implement classification algorithms and evaluation metrics from scratch in C++, including k-NN, Naive Bayes, decision trees, Logistic Regression, and ROC AUC.

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

Classification Algorithms

This course introduces common classification techniques and algorithms in order to predict the value of the class label based on the features in the dataset. We will discuss four different classificat

• INE
• 4 hours
• Self-Paced
• Paid Course

Supervised Learning in R: Classification

147 ratings at DataCamp

This beginner-level introduction to machine learning covers four of the most common classification algorithms.

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

Great Learning

Application of Classification Algorithms

Compare six supervised classification algorithms and evaluate their performance on a promotion-prediction case study.

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

Cracking Classification

Learn to compare and tune logistic regression, decision tree, KNN, Naive Bayes, and SVM classifiers using performance metrics.

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

Supervised Machine Learning: Classification

469 ratings at Coursera

Train classification models — logistic regression, k-nearest neighbors, support vector machines, decision trees and tree ensembles — and handle unbalanced classes with oversampling and undersampling.

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

Classification Analysis

Build and compare classifiers — KNN, decision trees, SVM, naive Bayes, and logistic regression — and evaluate them with accuracy, precision, recall, F1, and ROC curves.

• Coursera
• 6 weeks, 6 hours a week
• Self-Paced
• Paid Course

Great Learning

Supervised Machine Learning Tutorial - Logistic Regression - Naive Bayes Classifier

Learn how logistic regression and Naive Bayes classify data using probabilistic and linear approaches.

• YouTube
• 2 hours 58 minutes
• Self-Paced
• Free Video

Great Learning

Classification Algorithm Tutorial - Machine Learning Tutorial

Learn how supervised classification algorithms assign new observations to labeled categories such as spam or not spam.

• YouTube
• 9 hours 40 minutes
• Self-Paced
• Free Video

Weights & Biases

Label Factory - LLMs for Training Small Language Classification Models at Scale

Discover how to create small, multimodal classifiers using LLMs for content moderation at scale, achieving 90%+ accuracy without human annotation through knowledge distillation.

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

Kaggle;  Amazon Web Services

Supervised Learning

In this course, you'll learn about different types of supervised learning and how to use them to solve real-world problems.

• Udacity
• 17 hours
• Self-Paced
• Paid Course

BSidesLV

Repurposing Vulnerability Tickets to Predict Severity Levels - An Introduction to Natural Language Processing and Classification Algorithms

Repurpose vulnerability tickets as text data to predict severity levels with natural language processing and classification algorithms.

• YouTube
• 48 minutes
• Self-Paced
• Conference Talk

Career Certificate

Implementing AI Algorithms from Scratch in C++ (Part 1)

Implement core machine learning algorithms from scratch in C++, including regression, classification, and gradient-descent optimization.

• CodeSignal
• 13 hours
• Self-Paced
• Free Certificate
• 3 courses

Alberta Machine Intelligence Institute

Machine Learning Algorithms: Supervised Learning Tip to Tail

417 ratings at Coursera

Implement decision trees, k-NN, regression and support vector machines in Jupyter notebooks, then compare model performance and data preparation choices on business case studies.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course