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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 Trial
    Free Trial
    U

    University of Pennsylvania

    Intro to Predictive Analytics Using Python

    Skills you'll gain: Feature Engineering, Unsupervised Learning, Model Evaluation, Predictive Modeling, Predictive Analytics, Advanced Analytics, Decision Tree Learning, Supervised Learning, Applied Machine Learning, Model Training, Forecasting, Random Forest Algorithm, Analytics, Data Analysis, Regression Analysis, Machine Learning, Logistic Regression, Python Programming

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Machine Learning Models in Science

    Skills you'll gain: Data Preprocessing, Applied Machine Learning, Data Processing, Dimensionality Reduction, Data Cleansing, Machine Learning Algorithms, Data Transformation, Machine Learning Methods, Artificial Neural Networks, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Unsupervised Learning, Supervised Learning, Classification Algorithms, Predictive Modeling, Python Programming

    3.9
    Rating, 3.9 out of 5 stars
    ·
    15 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    Y

    Yale University

    Tropical Forest Landscapes 101: Conservation & Restoration

    Skills you'll gain: Land Management, Environmental Science, Sustainable Systems, Sustainable Development, Environment, Natural Resource Management, Environmental Engineering and Restoration, Environmental Issue, Environmental Resource Management, Environment and Resource Management, Philanthropy, Social Studies, Climate Change Mitigation, Socioeconomics, Finance, Financial Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    180 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    G

    Georgia Institute of Technology

    Fundamentals of Engineering Exam Review

    Skills you'll gain: Structural Analysis, Probability & Statistics, Structural Engineering, Hydraulics, Statistical Methods, Statistics, Engineering Analysis, Mechanical Engineering, Probability, Engineering, General Mathematics, Probability Distribution, Mechanics, Hydrology, Engineering Calculations, Engineering Practices, Civil Engineering, Applied Mathematics, Algebra, Calculus

    4.7
    Rating, 4.7 out of 5 stars
    ·
    616 reviews

    Mixed · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    Edureka

    Applied Machine Learning Without Coding

    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

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Build Predictive & Supervised Models

    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

  • Status: Preview
    Preview
    E

    EDUCBA

    R: Design & Evaluate Random Forests for Attrition

    Skills you'll gain: Model Evaluation, Data Preprocessing, Model Optimization, People Analytics, Model Training, Workforce Management, Classification Algorithms

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Introduction to Machine Learning in Sports Analytics

    Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Model Evaluation, Machine Learning Methods, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Machine Learning Software, Analytics, Decision Tree Learning, Machine Learning, Logistic Regression, Data Analysis, Data Analysis Software, Classification Algorithms, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    27 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Statistical Programming, Data Analysis, Probability, Statistics, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Game Theory

    Skills you'll gain: Game Theory, Mathematical Modeling, Bayesian Statistics, Behavioral Economics, Probability, Economics, Markov Model, Problem Solving, Algorithms, Correlation Analysis, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.9K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Probability, Statistical Inference, Statistics, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Correlation Analysis, Histogram, Statistical Visualization, Box Plots

    4.6
    Rating, 4.6 out of 5 stars
    ·
    689 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Analysis, Statistical Machine Learning, Statistical Visualization, Data Collection, Probability Distribution, Correlation Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

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In summary, here are 10 of our most popular random forest courses

  • Intro to Predictive Analytics Using Python: University of Pennsylvania
  • Machine Learning Models in Science: LearnQuest
  • Tropical Forest Landscapes 101: Conservation & Restoration: Yale University
  • Fundamentals of Engineering Exam Review: Georgia Institute of Technology
  • Applied Machine Learning Without Coding: Edureka
  • Build Predictive & Supervised Models: Coursera
  • R: Design & Evaluate Random Forests for Attrition: EDUCBA
  • Introduction to Machine Learning in Sports Analytics: University of Michigan
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Game Theory: Stanford University

Skills you can learn in Machine Learning

Python Programming (33)
Tensorflow (32)
Deep Learning (30)
Artificial Neural Network (24)
Big Data (18)
Statistical Classification (17)
Reinforcement Learning (13)
Algebra (10)
Bayesian (10)
Linear Algebra (10)
Linear Regression (9)
Numpy (9)

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