Random Forest Courses
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.
Popular Random Forest Courses and Certifications
Skills you'll gain: Matplotlib, Applied Machine Learning, Random Forest Algorithm, Predictive Modeling, Predictive Analytics, Machine Learning Algorithms, Data Visualization, Machine Learning, Programming Principles, Data Manipulation, Feature Engineering, Data Cleansing, Supervised Learning, Python Programming, Data Science, Data Processing, NumPy, Pandas (Python Package)
Status: Free TrialMultiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
Status: Free TrialSkills you'll gain: Feature Engineering, Applied Machine Learning, Advanced Analytics, Machine Learning, Unsupervised Learning, Workflow Management, Data Ethics, Supervised Learning, Data Validation, Classification And Regression Tree (CART), Random Forest Algorithm, Decision Tree Learning, Python Programming, Performance Tuning
Status: NewStatus: Free TrialSkills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Linear Algebra, Applied Machine Learning, Unsupervised Learning, Regression Analysis, Statistical Methods, Artificial Intelligence and Machine Learning (AI/ML)
Status: Free TrialSkills you'll gain: Data Storytelling, Data Visualization, Data Ethics, Exploratory Data Analysis, Sampling (Statistics), Data Presentation, Data Visualization Software, Feature Engineering, Regression Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Advanced Analytics, Data Analysis, Tableau Software, Data Science, Statistical Analysis, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, Python Programming
Status: Free TrialSkills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric
What brings you to Coursera today?
Status: Free TrialUniversity of Michigan
Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis
Status: Free TrialJohns Hopkins University
Skills you'll gain: Predictive Modeling, Machine Learning Algorithms, Feature Engineering, Supervised Learning, Classification And Regression Tree (CART), Predictive Analytics, Applied Machine Learning, R Programming, Machine Learning, Random Forest Algorithm, Regression Analysis, Data Processing, Data Collection
Status: Free TrialLearnQuest
Skills you'll gain: Random Forest Algorithm, Keras (Neural Network Library), Classification And Regression Tree (CART), Tensorflow, Deep Learning, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Supervised Learning, Machine Learning, Regression Analysis, Python Programming
Status: NewStatus: PreviewSkills you'll gain: Supervised Learning, Random Forest Algorithm, Applied Machine Learning, Data Processing, Classification And Regression Tree (CART), Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Predictive Modeling, Performance Testing, Data Analysis, Scikit Learn (Machine Learning Library), Python Programming
Status: Free TrialDeepLearning.AI
Skills you'll gain: Classification And Regression Tree (CART), Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning
Status: Free TrialUniversity of Washington
Skills you'll gain: Unsupervised Learning, Supervised Learning, Predictive Analytics, Statistical Modeling, R Programming, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Network Analysis, Big Data, Sampling (Statistics), Random Forest Algorithm
In summary, here are 10 of our most popular random forest courses
- Machine Learning: Random Forest with Python from Scratch©: Packt
- Machine Learning:Â DeepLearning.AI
- The Nuts and Bolts of Machine Learning:Â Google
- AI Machine Learning with R & Python Projects:Â EDUCBA
- Google Advanced Data Analytics:Â Google
- Supervised Machine Learning: Classification:Â IBM
- Applied Machine Learning in Python:Â University of Michigan
- Practical Machine Learning:Â Johns Hopkins University
- Neural Networks and Random Forests:Â LearnQuest
- Python: Implement & Evaluate Random Forests for ML:Â EDUCBA
