Random Forest courses can help you learn decision tree algorithms, ensemble methods, feature selection, and model evaluation techniques. You can build skills in data preprocessing, hyperparameter tuning, and interpreting model outputs. Many courses introduce tools like Python's scikit-learn and R's randomForest package, showing how these skills are applied to tasks such as classification, regression, and handling large datasets.

Skills you'll gain: Model Evaluation, Decision Tree Learning, Data Preprocessing, Data Manipulation, Statistical Modeling, R Programming, Supervised Learning, Machine Learning, Classification Algorithms
Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Data-Driven Decision-Making, Statistical Modeling, Classification Algorithms, Plot (Graphics)
Mixed · Course · 1 - 4 Weeks

Vanderbilt University
Skills you'll gain: Statistical Methods, Statistical Analysis, Data Visualization, Generative AI, Statistical Hypothesis Testing, Data Presentation, Data Storytelling, Box Plots, Data Analysis, Plot (Graphics), Data-Driven Decision-Making, Statistics, Technical Communication, Statistical Inference, Graphing
Beginner · Course · 1 - 4 Weeks
Coursera
Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Classification Algorithms, Java, Java Programming, Machine Learning Algorithms, Supervised Learning, Algorithms, Machine Learning, Data Structures, Software Engineering
Advanced · Course · 1 - 4 Weeks

Skills you'll gain: Artificial Neural Networks, Data Visualization, Exploratory Data Analysis, Data Presentation, Applied Machine Learning, Classification Algorithms, Machine Learning Methods, Predictive Modeling, Deep Learning, Classification And Regression Tree (CART), Data Analysis, Predictive Analytics, Machine Learning Algorithms, Model Evaluation, Machine Learning, Feature Engineering, Python Programming
Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Decision Tree Learning, Data Preprocessing, Data Transformation, Supervised Learning, Feature Engineering, Scikit Learn (Machine Learning Library), Classification Algorithms, Model Evaluation, Pandas (Python Package)
Intermediate · Guided Project · Less Than 2 Hours

Google Cloud
Skills you'll gain: Model Deployment, Fraud detection, Feature Engineering, Exploratory Data Analysis, Model Evaluation, Real Time Data, Applied Machine Learning, MLOps (Machine Learning Operations), Jupyter, Data Analysis, Data Preprocessing, Machine Learning
Beginner · Project · Less Than 2 Hours

Skills you'll gain: Scikit Learn (Machine Learning Library), Tensorflow, Classification Algorithms, Supervised Learning, Applied Machine Learning, Python Programming, Feature Engineering, Data Preprocessing, Data Science, Machine Learning, Model Evaluation, Data Manipulation, Data Visualization
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Dimensionality Reduction, R Programming, Time Series Analysis and Forecasting, Applied Machine Learning, Unsupervised Learning, Predictive Modeling, Machine Learning, Text Mining, Classification Algorithms, Artificial Neural Networks, Data Mining, Feature Engineering, Data Preprocessing, Model Evaluation, Exploratory Data Analysis
Mixed · Course · 1 - 4 Weeks

Skills you'll gain: Model Evaluation, Data Preprocessing, Exploratory Data Analysis, Feature Engineering, Model Deployment, Data Analysis, PySpark, Data Import/Export, Data Transformation, Apache Spark, Decision Tree Learning, Customer Analysis, Predictive Modeling, Predictive Analytics, Machine Learning
Intermediate · Guided Project · Less Than 2 Hours

Vanderbilt University
Skills you'll gain: Data Presentation, Regression Analysis, Statistical Analysis, Statistical Reporting, Correlation Analysis, Technical Communication, Probability & Statistics, Scatter Plots, Data Analysis, Predictive Analytics, Generative AI, Statistical Modeling
Intermediate · Course · 1 - 4 Weeks

O.P. Jindal Global University
Skills you'll gain: Anomaly Detection, Dimensionality Reduction, Unsupervised Learning, Customer Analysis, Marketing Analytics, Data Mining, Feature Engineering, Autoencoders, Applied Machine Learning, Machine Learning Algorithms, Machine Learning Methods, Marketing, Statistical Machine Learning, Target Audience, Python Programming, Market Analysis, Exploratory Data Analysis, Model Evaluation, Algorithms
Beginner · Course · 1 - 3 Months