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  • Random Forest

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


  • T

    The Hong Kong University of Science and Technology

    Python and Statistics for Financial Analysis

    Skills you'll gain: Statistical Inference, Portfolio Risk, Statistical Methods, Pandas (Python Package), Statistical Hypothesis Testing, Probability & Statistics, Risk Analysis, Financial Trading, Financial Data, Data Manipulation, Statistical Analysis, Feature Engineering, Regression Analysis, Financial Analysis, Jupyter, Financial Market, Market Data, Predictive Modeling, Python Programming, Data Visualization

    ★ 4.4 (4.6K) · Intermediate · Course · 1 - 4 Weeks

  • S

    Simplilearn

    Supervised Learning Regression Classification Clustering

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Machine Learning Methods, Classification Algorithms, Machine Learning Algorithms, Machine Learning, Predictive Modeling, Decision Tree Learning, Predictive Analytics, Logistic Regression, Random Forest Algorithm

    Beginner · Course · 1 - 4 Weeks

  • U

    University of Colorado Boulder

    Probability Foundations for Data Science and AI

    Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistics, Sampling (Statistics), Data Analysis, Correlation Analysis, Statistical Analysis, Statistical Inference

    ★ 4.5 (288) · Intermediate · Course · 1 - 3 Months

  • D

    Duke University

    Introduction to Probability and Data with R

    Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Probability & Statistics, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Methods, Statistical Analysis, Statistical Software, Descriptive Statistics

    ★ 4.7 (5.9K) · Beginner · Course · 1 - 3 Months

  • 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 (27) · Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    AI Workflow: Machine Learning, Visual Recognition and NLP

    Skills you'll gain: Model Evaluation, Tensorflow, Model Training, Supervised Learning, Model Optimization, Artificial Neural Networks, Regression Analysis, Applied Machine Learning, Statistical Machine Learning, Machine Learning Algorithms, Deep Learning, Image Analysis, Machine Learning, Random Forest Algorithm, AI Workflows, Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Data Science, Python Programming

    ★ 4.4 (92) · Advanced · Course · 1 - 4 Weeks

  • 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

  • U

    University of Michigan

    Understanding and Visualizing Data with Python

    Skills you'll gain: Sampling (Statistics), Data Visualization, Plot (Graphics), Statistics, Matplotlib, Statistical Visualization, Statistical Programming, Seaborn, Probability & Statistics, Jupyter, Statistical Methods, Data Visualization Software, Data Analysis, Statistical Analysis, Exploratory Data Analysis, Descriptive Statistics, Statistical Inference, Data Collection, NumPy, Python Programming

    ★ 4.7 (2.7K) · Beginner · Course · 1 - 4 Weeks

  • 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, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations

    Intermediate · Course · 1 - 3 Months

  • U

    University of Pennsylvania

    Modeling Risk and Realities

    Skills you'll gain: Risk Modeling, Risk Management, Mathematical Modeling, Statistical Modeling, Predictive Modeling, Risk Analysis, Data Modeling, Simulation and Simulation Software, Statistical Methods, Probability Distribution, Statistics, Data-Driven Decision-Making, Decision Making, Statistical Hypothesis Testing, Model Optimization, Microsoft Excel, Spreadsheet Software

    ★ 4.6 (2.2K) · Mixed · Course · 1 - 4 Weeks

  • E

    EDUCBA

    Machine Learning with Python & Statistics

    Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Statistical Machine Learning, Probability & Statistics, Linear Algebra, Statistical Methods, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Data Science, Statistics, Machine Learning Methods, Applied Machine Learning, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning

    Mixed · Course · 1 - 4 Weeks

  • C

    Coursera

    Automate Financial Analysis with AI Pipelines

    Skills you'll gain: Model Evaluation, Model Training, Forecasting, Financial Data, Financial Forecasting, Performance Metric, Financial Analysis, Credit Risk, AI Integrations, Applied Machine Learning, AI Workflows, Data Pipelines, Artificial Neural Networks, Automation

    Intermediate · Course · 1 - 4 Weeks

1…678…44

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

  • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
  • Supervised Learning Regression Classification Clustering: Simplilearn
  • Probability Foundations for Data Science and AI: University of Colorado Boulder
  • Introduction to Probability and Data with R: Duke University
  • Introduction to Machine Learning in Sports Analytics: University of Michigan
  • AI Workflow: Machine Learning, Visual Recognition and NLP: IBM
  • R: Design & Evaluate Random Forests for Attrition: EDUCBA
  • Understanding and Visualizing Data with Python: University of Michigan
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Modeling Risk and Realities: University of Pennsylvania

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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