Random Forests Courses and Certifications

Introduction to Machine Learning in Sports Analytics

27 ratings at Coursera

Explore supervised machine learning techniques using Python and real athletic data to predict sports outcomes, applying methods like SVM, decision trees, and ensembles to analyze professional leagues and wearable device data.

• Coursera
• 12 hours 55 minutes
• Self-Paced
• Paid Course

AI for Medical Prognosis

800 ratings at Coursera

In this course, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis.

• Coursera
• 1 day 5 hours 44 minutes
• Self-Paced
• Paid Course

Introduction to AI: Key Concepts and Applications

25 ratings at Coursera

Master essential AI foundations, from R.O.A.D framework to algorithm selection, data quality, and performance metrics. Gain practical insights for evaluating and implementing AI systems while balancing technical depth with strategic decision-making.

• Coursera
• 19 hours 58 minutes
• Self-Paced
• Paid Course

Python Machine Learning Bootcamp (Live Online)

749 ratings at CourseHorse

Master the in-demand skill of machine learning and learn how to create algorithms that can independently learn patterns and make decisions in this hands-on bootcamp.

• CourseHorse
• Self-Paced
• $1,895.00

Advanced Methods in Machine Learning Applications

Master advanced machine learning techniques for complex problem-solving. Explore ensemble learning, regression analysis, unsupervised learning, and reinforcement learning. Gain practical skills to implement and optimize sophisticated models.

• Coursera
• 19 hours 58 minutes
• Self-Paced
• Paid Course

Python Machine Learning Bootcamp (Live Online)

686 ratings at CourseHorse

Master the practical skills needed to solve real-world problems with machine learning.

• CourseHorse
• Self-Paced
• $1,895.00

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

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

Introduction to Machine Learning: Supervised Learning

24 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

Ensemble Machine Learning in Python: Random Forest, AdaBoost

2654 ratings at Udemy

Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python

• Udemy
• 5 hours 48 minutes
• Self-Paced
• Paid Course

H2O.ai

Practical Machine Learning on H2O

74 ratings at Coursera

Learn core machine learning techniques using H2O, including linear models, random forests, GBMs, and deep learning. Evaluate and choose optimal models for your data and business constraints.

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

The Supervised Machine Learning Bootcamp

1428 ratings at Udemy

Data Science, Python, sk learn, Decision Trees, Random Forests, KNNs, Ridge Lasso Regression, SVMs

• Udemy
• 5 hours 49 minutes
• Self-Paced
• Paid Course

Coursera

Mining Quality Prediction Using Machine & Deep Learning

69 ratings at Coursera

Predict silica concentrate in iron ore using machine learning and deep learning models. Explore data, train models, and evaluate performance for faster mining industry predictions.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Coursera

Interpretable Machine Learning Applications: Part 4

23 ratings at Coursera

Explore interpretable machine learning using Google's What-If Tool. Learn to analyze and visualize prediction model behavior for white wine quality classification using Decision Trees and Random Forests.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Coursera

Scikit-Learn For Machine Learning Classification Problems

19 ratings at Coursera

Learn to build and train classifier models using Scikit-Learn, exploring algorithms for classification, regression, and clustering, including support vector machines, random forests, and k-means.

• Coursera
• 1 hour 48 minutes
• Self-Paced
• Paid Course