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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


  • E

    EDUCBA

    PySpark: Apply & Evaluate Predictive ML Models

    Skills you'll gain: Model Evaluation, PySpark, Apache Spark, Logistic Regression, Predictive Modeling, Applied Machine Learning, Unsupervised Learning, Decision Tree Learning, Predictive Analytics, Advanced Analytics, Machine Learning Methods, Random Forest Algorithm, Model Training, Regression Analysis, Classification Algorithms, Machine Learning Algorithms, Data Pipelines

    5
    Rating, 5 out of 5 stars
    ·
    12 reviews

    Mixed · Course · 1 - 4 Weeks

  • 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

  • E

    Edureka

    Applied Machine Learning with Python

    Skills you'll gain: Model Evaluation, Supervised Learning, Machine Learning Methods, AI Personalization, Classification Algorithms, Machine Learning, Model Training, Logistic Regression, Model Optimization, Data Analysis, Driving engagement, Persona (User Experience)

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Intermediate Data Manipulation and Machine Learning

    Skills you'll gain: Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Classification Algorithms, Reinforcement Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Dimensionality Reduction, Statistical Analysis, Supervised Learning, Unsupervised Learning, Data Preprocessing, Data Mining, Predictive Modeling, Random Forest Algorithm, Logistic Regression, Model Optimization, Data Manipulation

    Intermediate · Course · 3 - 6 Months

  • U

    University of California, Santa Cruz

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Time Series Analysis and Forecasting, Statistical Inference, Statistical Methods, R Programming, Forecasting, Statistical Programming, Probability & Statistics, Statistical Modeling, Technical Communication, Data Presentation, Probability, Statistics, Statistical Analysis, Statistical Reporting, Statistical Software, Probability Distribution, Data Analysis, Markov Model, Data Science

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.5K reviews

    Intermediate · Specialization · 3 - 6 Months

  • P

    Packt

    Advanced ML Algorithms & Unsupervised Learning

    Skills you'll gain: Model Optimization, Dimensionality Reduction, Unsupervised Learning, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Anomaly Detection, Classification Algorithms, Linear Algebra

    Intermediate · 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

    Build Robust Java ML Models with Entropy

    Skills you'll gain: Model Evaluation, Model Deployment, Model Training, Decision Tree Learning, Data Preprocessing, Java Programming, Classification Algorithms, Predictive Modeling, Random Forest Algorithm, Applied Machine Learning, Java, Program Evaluation, Machine Learning Methods, Machine Learning Algorithms, Machine Learning, Algorithms, Program Implementation, Business Development

    Advanced · 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

  • P

    Packt

    Regression Analysis for Statistics & Machine Learning in R

    Skills you'll gain: Data Cleansing, Data Wrangling, R Programming, Data Preprocessing, Applied Machine Learning, Statistical Analysis, R (Software), Model Evaluation, Statistical Machine Learning, Classification And Regression Tree (CART), Statistical Programming, Statistical Modeling, Logistic Regression, Machine Learning Methods, Random Forest Algorithm, Data Transformation, Statistical Methods, Model Training, Predictive Modeling, Machine Learning

    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
    Rating, 4.7 out of 5 stars
    ·
    5.9K reviews

    Beginner · Course · 1 - 3 Months

  • R

    Rice University

    Business Statistics and Analysis

    Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Statistical Methods, Pivot Tables And Charts, Regression Analysis, Data Literacy, Statistics, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Modeling, Statistical Analysis, Statistical Inference, Excel Formulas, Data Analysis, Presentations, Sample Size Determination

    4.7
    Rating, 4.7 out of 5 stars
    ·
    13K reviews

    Beginner · Specialization · 3 - 6 Months

1…678…44

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

  • PySpark: Apply & Evaluate Predictive ML Models: EDUCBA
  • ML: Build, Train, Justify Models: Coursera
  • Applied Machine Learning with Python: Edureka
  • Intermediate Data Manipulation and Machine Learning: Packt
  • Bayesian Statistics: University of California, Santa Cruz
  • Advanced ML Algorithms & Unsupervised Learning: Packt
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University
  • Build Robust Java ML Models with Entropy: Coursera
  • Automate Financial Analysis with AI Pipelines: Coursera
  • Regression Analysis for Statistics & Machine Learning in R: Packt

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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