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
Multiple 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)
Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms
University 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
Johns 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: Hands-On ProjectsSkills you'll gain: Data Storytelling, Data Visualization, A/B Testing, Sampling (Statistics), Data Analysis, Exploratory Data Analysis, Regression Analysis, Data Visualization Software, Data Presentation, Data Ethics, Feature Engineering, Statistical Hypothesis Testing, Statistics, Statistical Analysis, Data Science, Tableau Software, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, Python Programming
What brings you to Coursera today?
LearnQuest
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
DeepLearning.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
Skills 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
University 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
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
Johns 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
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
- Applied Machine Learning in Python:Â University of Michigan
- Practical Machine Learning:Â Johns Hopkins University
- Google Advanced Data Analytics:Â Google
- Neural Networks and Random Forests:Â LearnQuest
- Advanced Learning Algorithms:Â DeepLearning.AI
- Python: Implement & Evaluate Random Forests for ML:Â EDUCBA
- Trees, SVM and Unsupervised Learning:Â University of Colorado Boulder
