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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


  • 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

  • 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

  • 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

  • U

    University of Amsterdam

    Quantitative Methods

    Skills you'll gain: Scientific Methods, Research Design, Sampling (Statistics), Science and Research, Research, Research Methodologies, Surveys, Quantitative Research, Data Collection, Social Sciences, Survey Creation, Experimentation, Ethical Standards And Conduct

    ★ 4.7 (2.4K) · Mixed · Course · 1 - 3 Months

  • 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

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

  • 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

  • S

    Stanford University

    Social and Economic Networks: Models and Analysis

    Skills you'll gain: Social Network Analysis, Network Analysis, Social Sciences, Sociology, Socioeconomics, Game Theory, Behavioral Economics, Mathematical Modeling, Statistical Modeling, Bayesian Statistics, Probability

    ★ 4.8 (759) · Advanced · Course · 1 - 3 Months

  • J

    Johns Hopkins University

    Advanced Methods in Machine Learning Applications

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    ML: Build, Train, Justify Models

    Skills you'll gain: Model Training, Predictive Modeling, Applied Machine Learning, Machine Learning Methods, Statistical Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Statistical Modeling, Predictive Analytics, Technical Communication

    Intermediate · Course · 1 - 4 Weeks

  • 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 Pennsylvania

    Introduction to Spreadsheets and Models

    Skills you'll gain: Spreadsheet Software, Financial Modeling, Predictive Modeling, Regression Analysis, Statistical Modeling, Data Modeling, Financial Forecasting, Excel Formulas, Risk Modeling, Business Modeling, Simulation and Simulation Software, Microsoft Excel, Google Sheets, Probability Distribution, Analysis, Forecasting, Predictive Analytics, Risk Analysis, Statistical Methods, Data Analysis Software

    ★ 4.2 (3.9K) · Mixed · Course · 1 - 4 Weeks

1…678…44

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

  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Automate Financial Analysis with AI Pipelines: Coursera
  • Introduction to Machine Learning in Sports Analytics: University of Michigan
  • Quantitative Methods: University of Amsterdam
  • Machine Learning with Python & Statistics: EDUCBA
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Modeling Risk and Realities: University of Pennsylvania
  • Social and Economic Networks: Models and Analysis: Stanford University
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University
  • ML: Build, Train, Justify Models: Coursera

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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