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: Cascading Style Sheets (CSS), Hypertext Markup Language (HTML), User Interface (UI), User Experience Design, Web Design and Development, Development Environment, Front-End Web Development, Javascript, Web Development, Web Applications, Responsive Web Design, Microsoft Visual Studio, Real Time Data, Data Validation
Beginner · Course · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations
Intermediate · Course · 1 - 3 Months
Stanford University
Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis
Advanced · Course · 1 - 3 Months

Yale University
Skills you'll gain: Land Management, Environmental Science, Sustainable Development, Environment, Natural Resource Management, Environmental Engineering and Restoration, Environment and Resource Management, Climate Change Mitigation, Socioeconomics, Finance
Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Cleansing, Sampling (Statistics), Data Integrity, Data Quality, Data Processing, Data Analysis, Data Transformation, Data Validation, Sample Size Determination, SQL, Spreadsheet Software
Beginner · Course · 1 - 3 Months

Skills you'll gain: Model Evaluation, Supervised Learning, Machine Learning Methods, Classification Algorithms, Machine Learning, Data Analysis, Driving engagement
Intermediate · Course · 1 - 4 Weeks

Northeastern University
Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Reinforcement Learning, Supervised Learning, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Decision Tree Learning, Classification Algorithms, Random Forest Algorithm, Autoencoders, Predictive Modeling, Feature Engineering
Intermediate · Course · 1 - 3 Months
University of Michigan
Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Model Evaluation, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Decision Tree Learning, Machine Learning, Logistic Regression, Data Analysis, Classification Algorithms, Data Preprocessing, Python Programming
Intermediate · Course · 1 - 4 Weeks

University of London
Skills you'll gain: Education Software and Technology, Learning Management Systems, Collaboration, Digital pedagogy, Discussion Facilitation, Graphical Tools, Test Tools
Beginner · Course · 1 - 4 Weeks

University of Amsterdam
Skills you'll gain: Scientific Methods, Research Design, Sampling (Statistics), Science and Research, Research, Research Methodologies, Surveys, Quantitative Research, Social Sciences, Experimentation, Ethical Standards And Conduct
Mixed · Course · 1 - 3 Months
University of Washington
Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Bioinformatics, Mathematical Modeling, Physiology, Recurrent Neural Networks (RNNs), Biology, Linear Algebra, Statistical Methods, Information Architecture, Differential Equations, Probability Distribution
Beginner · Course · 1 - 3 Months

Skills you'll gain: Model Evaluation, Unsupervised Learning, Deep Learning, Autoencoders, Anomaly Detection, Applied Machine Learning, Machine Learning, Supervised Learning, Decision Tree Learning, Predictive Modeling, Classification Algorithms, Data Preprocessing, Random Forest Algorithm, Data Manipulation, Feature Engineering, Dimensionality Reduction
Intermediate · Course · 1 - 3 Months