Free Online Random Forest Courses & MOOCs

Coursera

H2O.ai

Practical Machine Learning on H2O (Coursera)

Data Science

Embark on a transformative journey into the world of machine learning with Practical Machine Learning on H2O. This course is designed for those new to data science, aiming to empower learners with the skills needed to create effective machine learning models using H2O's powerful open-source platform. From linear models and random forests to gradient boosting machines (GBMs) and deep learning, this course covers a broad spectrum of algorithms, ensuring you're well-equipped to tackle various data challenges.

Aug 17th 2026

5-12 Weeks

Machine Learning Data Science Linear Models

Coursera

Wesleyan University

Machine Learning for Data Analysis (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of machine learning and transform raw data into actionable insights with our Machine Learning for Data Analysis course. This course builds upon foundational concepts introduced in Course 3, expanding your knowledge to include classification, decision trees, clustering, and more. Perfect for data enthusiasts looking to harness predictive power.

Aug 10th 2026

4 Weeks

Python Machine Learning Data Analysis

Coursera

LearnQuest

Machine Learning Models in Science (Coursera)

Data Science

Embark on a journey into the world of applying machine learning techniques to solve complex scientific challenges. This course will guide you through every step of the machine learning pipeline, from data cleaning and transformation to running advanced algorithms. Perfect for scientists, researchers, and anyone interested in leveraging AI for problem-solving.

Aug 10th 2026

4 Weeks

Algorithms Machine Learning Neural Networks

Coursera

LearnQuest

Neural Networks and Random Forests (Coursera)

Data Science

Dive deep into the world of advanced artificial intelligence with our 'Neural Networks and Random Forests' course. Learn to construct sophisticated neural network models and random forest algorithms from scratch, understanding their structures and properties thoroughly. This course will equip you with essential skills in avoiding overfitting, regularization techniques, and optimizing hyper-parameters for effective model performance.

Aug 10th 2026

3 Weeks

Neural Networks AI Random Forest

Coursera

University of Michigan

Introduction to Machine Learning in Sports Analytics (Coursera)

Statistics & Data Analysis Data Science

Dive deep into the world of sports analytics with our Introduction to Machine Learning in Sports Analytics course. Gain expertise in applying machine learning techniques using Python's scikit-learn toolkit on real-world athletic datasets. Explore various algorithms and learn how to predict outcomes in professional sports, enhancing your understanding and skills in data analysis.

Aug 10th 2026

4 Weeks

Machine Learning Linear Regression Logistic Regression

Coursera

University of Colorado Boulder

Introduction to Machine Learning: Supervised Learning (Coursera)

Data Science

Embark on a journey into the world of supervised machine learning with this foundational online course. Designed for beginners and advanced learners alike, you'll delve into essential algorithms like linear and logistic regression, K-nearest neighbors (KNN), decision trees, random forest, boosting techniques, and kernel methods such as support vector machines (SVM). This course is perfect for those looking to harness the predictive power of data.

Aug 10th 2026

5-12 Weeks

ML Machine Learning Linear Regression

Coursera

Google

The Nuts and Bolts of Machine Learning (Coursera)

Data Science

Dive into 'The Nuts and Bolts of Machine Learning' – a crucial part of Google's Advanced Data Analytics Certificate. This course will equip you with the skills needed to analyze large datasets, solve intricate issues, and make precise forecasts using advanced algorithms and statistical analysis.

Aug 10th 2026

5-12 Weeks

Python Machine Learning Clustering

Coursera

University of Colorado Boulder

Trees, SVM and Unsupervised Learning (Coursera)

Statistics & Data Analysis Data Science

Dive into 'Trees, SVM and Unsupervised Learning' - an advanced course designed to equip you with the skills needed to construct sophisticated predictive models using support vector machines (SVM), decision trees, neural networks, and XG boost. This course is perfect for data scientists and machine learning enthusiasts looking to expand their expertise in classification techniques.

Aug 10th 2026

4 Weeks

Statistics Regression Neural Networks

Coursera

Johns Hopkins University

Practical Machine Learning (Coursera)

Statistics & Data Analysis Data Science

Discover the essential skills needed for data science with our Practical Machine Learning course. Designed for beginners, this course will guide you through the basics of creating and implementing prediction models, focusing on real-world application and avoiding common pitfalls like overfitting and error rates.

Aug 3rd 2026

4 Weeks

Algorithms Machine Learning Regression