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.

Johns Hopkins University
Skills you'll gain: Probability & Statistics, Probability, Probability Distribution, Simulations, Statistical Modeling, Statistical Methods, Estimation, Correlation Analysis, Engineering Analysis, Statistical Analysis, Reliability, Engineering, Spatial Analysis
Mixed · Course · 1 - 4 Weeks

LearnQuest
Skills you'll gain: Data Preprocessing, Feature Engineering, Model Evaluation, Bioinformatics, Exploratory Data Analysis, Random Forest Algorithm, Pandas (Python Package), Scikit Learn (Machine Learning Library), Applied Machine Learning, Data Manipulation, Data Processing, Dimensionality Reduction, Data Cleansing, Model Optimization, Keras (Neural Network Library), Machine Learning Algorithms, Data Transformation, Model Training, Machine Learning, Data Science
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Data Science, Statistical Modeling, Predictive Modeling, Machine Learning Methods, Exploratory Data Analysis, Machine Learning, Data Analysis, Applied Machine Learning, Machine Learning Software, Feature Engineering, Random Forest Algorithm, Supervised Learning, Logistic Regression, Data Processing, Model Optimization, Data Manipulation, Data Visualization
Intermediate · Course · 1 - 4 Weeks

University of Amsterdam
Skills you'll gain: Qualitative Research, Scientific Methods, Statistical Analysis, Statistical Hypothesis Testing, Research, Science and Research, Research Design, Sampling (Statistics), Research Reports, Interviewing Skills, Data Analysis, Data Collection, Research Methodologies, Probability & Statistics, Social Sciences, Statistical Methods, Regression Analysis, Statistical Inference, Statistics, R Programming
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Spatial Data Analysis, Spatial Analysis, Geographic Information Systems, Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Matplotlib, Convolutional Neural Networks, Image Analysis, Applied Machine Learning, Plot (Graphics), Supervised Learning, Environmental Monitoring, Geospatial Information and Technology, Scientific Visualization, Predictive Modeling, Deep Learning, Geospatial Mapping, Machine Learning
Intermediate · Specialization · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning
Intermediate · Specialization · 1 - 3 Months

Skills you'll gain: Model Training, Model Optimization, Model Evaluation, Machine Learning Software, Applied Machine Learning, Predictive Modeling, Machine Learning Methods, Feature Engineering, Workflow Management, Verification And Validation, Machine Learning, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Scikit Learn (Machine Learning Library), Benchmarking, Random Forest Algorithm, Performance Analysis, Cost Management, Resource Utilization
Intermediate · Course · 1 - 3 Months

University of Alberta
Skills you'll gain: Reinforcement Learning, Machine Learning Methods, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Systems Development, Simulations, Solution Architecture, Agentic systems, Feature Engineering, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Decision Intelligence, Supervised Learning, Algorithms, Model Evaluation, Applied Machine Learning
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Large Language Modeling, Retrieval-Augmented Generation, LLM Application, Data Analysis, Applied Machine Learning, Keras (Neural Network Library), Machine Learning Methods, Model Evaluation, Model Training, Fine-tuning, Model Deployment, Generative AI, Text Mining, Prompt Engineering, Deep Learning, Random Forest Algorithm, Machine Learning, MLOps (Machine Learning Operations)
Intermediate · Course · 3 - 6 Months

Skills you'll gain: Anomaly Detection, MLOps (Machine Learning Operations), AI Security, Software Engineering, Model Training, DevOps, Software Quality Assurance, Maintainability, CI/CD, Model Deployment, Performance Tuning, Security Testing, Model Evaluation, Secure Coding, Performance Testing, Continuous Monitoring, Integration Testing, Data Validation, Sampling (Statistics), Python Programming
Intermediate · Course · 1 - 3 Months

Skills you'll gain: Model Training, Benchmarking, Decision Intelligence, Resource Utilization, Cost Estimation, Resource Consumption Accounting, Memory Management, Run Chart, Analysis, Cost Management
Intermediate · Course · 1 - 4 Weeks

Coursera
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Business Metrics, Model Training, Feature Engineering, Predictive Modeling, Random Forest Algorithm, Supervised Learning, Scikit Learn (Machine Learning Library), Performance Metric, Machine Learning Algorithms, Regression Analysis, Continuous Monitoring, Statistical Methods
Intermediate · Course · 1 - 4 Weeks