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
Status: Free TrialMultiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
Skills you'll gain: Matplotlib, Applied Machine Learning, Random Forest Algorithm, Predictive Modeling, Data Visualization, Data Preprocessing, Machine Learning, Data Manipulation, Feature Engineering, Data Cleansing, Python Programming, Data Science, Model Evaluation, Classification Algorithms, NumPy, Pandas (Python Package)
Status: Free TrialSkills you'll gain: Feature Engineering, Model Evaluation, Advanced Analytics, Statistical Machine Learning, Unsupervised Learning, Machine Learning, Data Ethics, Supervised Learning, Decision Tree Learning, Random Forest Algorithm, Classification Algorithms, Python Programming, Performance Tuning
Status: Free TrialSkills you'll gain: Data Storytelling, Data Visualization, Exploratory Data Analysis, Regression Analysis, Feature Engineering, Statistical Hypothesis Testing, Sampling (Statistics), Data Ethics, Logistic Regression, Model Evaluation, Data Visualization Software, Descriptive Statistics, Data Analysis, Statistical Analysis, Tableau Software, Object Oriented Programming (OOP), Data Science, Machine Learning, Interviewing Skills, Python Programming
Status: Free TrialJohns Hopkins University
Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Supervised Learning, Predictive Analytics, Applied Machine Learning, Data Preprocessing, R Programming, Classification Algorithms, Machine Learning, Random Forest Algorithm, Regression Analysis, Exploratory Data Analysis, Data Wrangling
Status: Free TrialUniversity of Colorado Boulder
Skills you'll gain: Model Evaluation, Applied Machine Learning, Unsupervised Learning, Classification And Regression Tree (CART), Decision Tree Learning, Artificial Neural Networks, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Random Forest Algorithm, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Statistics
What brings you to Coursera today?
Status: Free TrialLearnQuest
Skills you'll gain: Model Evaluation, Random Forest Algorithm, Keras (Neural Network Library), Tensorflow, Deep Learning, Artificial Neural Networks, Decision Tree Learning, Scikit Learn (Machine Learning Library), Machine Learning, Regression Analysis, Classification Algorithms, Python Programming
Status: NewStatus: PreviewSkills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Classification Algorithms, Predictive Modeling, Data Analysis, Python Programming
Status: Free TrialUniversity of Michigan
Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks
Status: Free TrialDeepLearning.AI
Skills you'll gain: Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Artificial Neural Networks, Logistic Regression, Performance Tuning
Status: PreviewJohns Hopkins University
Skills you'll gain: Probability & Statistics, Probability Distribution, Simulations, Statistical Modeling, Correlation Analysis, Engineering Analysis, Digital Signal Processing, Statistical Analysis, Reliability, Engineering, Spatial Analysis
Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Model Evaluation, Random Forest Algorithm, Responsible AI, Data Import/Export, Machine Learning, Classification Algorithms
In summary, here are 10 of our most popular random forest courses
- Machine Learning:Â DeepLearning.AI
- Machine Learning: Random Forest with Python from Scratch©: Packt
- The Nuts and Bolts of Machine Learning:Â Google
- Google Advanced Data Analytics:Â Google
- Practical Machine Learning:Â Johns Hopkins University
- Trees, SVM and Unsupervised Learning:Â University of Colorado Boulder
- Neural Networks and Random Forests:Â LearnQuest
- Python: Implement & Evaluate Random Forests for ML:Â EDUCBA
- Applied Machine Learning in Python:Â University of Michigan
- Advanced Learning Algorithms:Â DeepLearning.AI
