Classification Courses and Certifications

Coursera

Measure Vector Similarity

Master cosine similarity, dot-product, and Euclidean distance through hands-on Python implementation and real-world benchmarking for ML applications.

• Coursera
• 1 hour 49 minutes
• Self-Paced
• Paid Course

Coursera

ML Concepts, Models & Workflow Essentials

Master advanced machine learning in Java using Weka, Deeplearning4j, and Smile to build enterprise-grade predictive models, customer segmentation, and scalable MLOps solutions.

• Coursera
• 4 hours 36 minutes
• Self-Paced
• Paid Course

Coursera

Build & Evaluate Decision Trees for ML

Master decision tree algorithms in Java using Weka and Smile libraries. Build, tune, and evaluate models with entropy, Gini index, and cross-validation techniques for real-world ML applications.

• Coursera
• 4 hours 8 minutes
• Self-Paced
• Paid Course

Coursera

Design Taxonomy & Audit

Explore practical skills for designing scalable documentation taxonomies and conducting audits to improve search quality, consistency, and discoverability in HR and Finance knowledge bases.

• Coursera
• 2 hours
• Self-Paced
• Paid Course

EDUCBA

R: Design & Evaluate Random Forests for Attrition

Master Random Forest algorithms in R to predict employee attrition through hands-on model building, parameter tuning, and performance evaluation using real HR data.

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

EDUCBA

Master Decision Trees in R: Build, Predict & Evaluate

Discover how to build, interpret, and evaluate decision tree models in R for classification and regression using real-world datasets like bank loans and diabetes outcomes.

• Coursera
• 8 hours 8 minutes
• Self-Paced
• Paid Course

Coursera

Build Robust Java ML Models with Entropy

Master entropy-driven machine learning by building decision trees and random forests from scratch in Java, handling real-world data challenges and deploying production-ready ML systems.

• Coursera
• 3 hours 45 minutes
• Self-Paced
• Paid Course

EDUCBA

Analyze and Predict Card Purchases Using R

Master predictive modeling in R by analyzing customer data, building logistic regression and decision tree models, and evaluating performance to accurately predict card purchase behavior.

• Coursera
• 5 hours 24 minutes
• Self-Paced
• Paid Course

Performance measures and validation methods

Master rigorous ML model evaluation using ROC analysis, AUC, C-index, and advanced cross-validation strategies to build reliable, generalizable machine learning workflows.

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

Machine Learning Basics Camp (Ages 12-18) (Live Online)

Unlock the magic of data with Machine Learning Basics Camp—a hands-on adventure for ages 13–18 where students explore Python, dive into real-world data, and build their own machine-learning models.

• CourseHorse
• 15 hours
• Self-Paced
• $399.00

Understanding the World Through Data

Discover how to leverage data and basic machine learning algorithms using Python to explore relationships, distributions, and classification models for real-world insights.

• MITx Online
• 9 weeks, 3-6 hours a week
• Self-Paced
• Free Online Course

TensorFlow 2.0 Practical

961 ratings at Udemy

Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 10 practical projects

• Udemy
• 11 hours 45 minutes
• Self-Paced
• Paid Course

Dr. Najeeb Lectures

Hemolytic Anemia Classification in Hematology

2 ratings

Comprehensive exploration of hemolytic anemia, covering classification, causes, and mechanisms. Detailed breakdown of extra-erythrocytic disorders and red blood cell abnormalities leading to this condition.

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

Dr. Sam's Imaging Library

Mammography - Normal vs Abnormal Images and BI-RADS Classification for Breast Cancer and Other Diseases

3 ratings

Explore mammography images, distinguishing normal from abnormal findings. Learn BI-RADS classification and identify various breast conditions, from benign changes to malignancies.

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

Bag of Words Model for Image Classification - Lecture 16

Explore bag-of-features for image classification, including feature extraction, quantization, and spatial pyramid matching. Learn about datasets and applications in scene and action recognition.

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