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    • Random Forest

    Random Forest Courses Online

    Study random forest algorithms for machine learning. Learn to build and apply random forest models for classification and regression tasks.

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    Explore the Random Forest Course Catalog

    • C

      Coursera Project Network

      Interpretable Machine Learning Applications: Part 1

      Skills you'll gain: Feature Engineering, Classification And Regression Tree (CART), Decision Tree Learning, Applied Machine Learning, Random Forest Algorithm, Predictive Modeling, Data Import/Export, Data Analysis, Machine Learning, Data-Driven Decision-Making, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      50 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Data Analysis in R: Predictive Analysis with Regression

      Skills you'll gain: Ggplot2, Data Visualization, Regression Analysis, Predictive Analytics, Data-Driven Decision-Making, Statistical Modeling, R Programming, Descriptive Statistics, Exploratory Data Analysis, Statistics

      4.2
      Rating, 4.2 out of 5 stars
      ·
      13 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: New
      New
      M

      Microsoft

      Advanced Data Analysis with Generative AI

      Skills you'll gain: Generative AI, Anomaly Detection, Predictive Modeling, Text Mining, Predictive Analytics, Advanced Analytics, Data Cleansing, Prompt Engineering, Natural Language Processing, Unstructured Data, Data Analysis, Forecasting, Data Quality, Time Series Analysis and Forecasting, Exploratory Data Analysis, Software Documentation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Washington

      Practical Predictive Analytics: Models and Methods

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Big Data

      4.1
      Rating, 4.1 out of 5 stars
      ·
      320 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      Y

      Yale University

      Tropical Forest Landscapes 101: Conservation & Restoration

      Skills you'll gain: Land Management, Environmental Science, Environment, Natural Resource Management, Environmental Resource Management, Biology, Water Resources, Social Studies, Finance, Community Development

      4.9
      Rating, 4.9 out of 5 stars
      ·
      157 reviews

      Beginner · Course · 1 - 3 Months

    • A

      Alberta Machine Intelligence Institute

      Optimizing Machine Learning Performance

      Skills you'll gain: Data Ethics, MLOps (Machine Learning Operations), Business Operations, Machine Learning, Ethical Standards And Conduct, Operational Analysis, Applied Machine Learning, Business Strategy, Production Planning, Data Maintenance, Maintainability, Risk Mitigation, Performance Metric, Systems Integration, Stakeholder Communications

      4.4
      Rating, 4.4 out of 5 stars
      ·
      49 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Machine Learning Algorithms with R in Business Analytics

      Skills you'll gain: Regression Analysis, R Programming, Exploratory Data Analysis, Business Analytics, Statistical Analysis, Predictive Analytics, Unsupervised Learning, Machine Learning, Data Analysis, Classification And Regression Tree (CART), Data Mining, Supervised Learning

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      38 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      P

      Pontificia Universidad Católica de Chile

      Introducción a los modelos de demanda de transporte

      Skills you'll gain: Data Collection, Transportation Operations, Surveys, Quantitative Research, Mathematical Modeling, Predictive Modeling, Statistical Methods, Regression Analysis, Spatial Analysis, Probability Distribution, Probability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      458 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Predictive Analytics for Business with H2O in R

      Skills you'll gain: R Programming, Predictive Analytics, Applied Machine Learning, Data Science, Data Processing, Feature Engineering, Machine Learning, Telemarketing, Application Deployment

      4.9
      Rating, 4.9 out of 5 stars
      ·
      52 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • U

      Universidad de los Andes

      Fundamentos de estadística aplicada

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Methods, Data Analysis, Regression Analysis, Sampling (Statistics), Statistical Analysis, Probability & Statistics, Probability Distribution, Applied Mathematics, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      133 reviews

      Intermediate · Course · 1 - 3 Months

    • A

      American Psychological Association

      Methods for Quantitative Research in Psychology

      Skills you'll gain: Quantitative Research, Scientific Methods, Research Design, Surveys, Research, Correlation Analysis, Data Collection, Data Analysis, Psychology, Sampling (Statistics)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      155 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      T

      The Chinese University of Hong Kong

      Information Theory

      Skills you'll gain: Digital Communications, Theoretical Computer Science, Telecommunications, Information Management, Probability, Probability Distribution, Technical Communication, Algorithms, General Mathematics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      163 reviews

      Mixed · Course · 3 - 6 Months

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

    • Interpretable Machine Learning Applications: Part 1: Coursera Project Network
    • Data Analysis in R: Predictive Analysis with Regression: Coursera Project Network
    • Advanced Data Analysis with Generative AI: Microsoft
    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Tropical Forest Landscapes 101: Conservation & Restoration: Yale University
    • Optimizing Machine Learning Performance: Alberta Machine Intelligence Institute
    • Machine Learning Algorithms with R in Business Analytics: University of Illinois Urbana-Champaign
    • Introducción a los modelos de demanda de transporte: Pontificia Universidad Católica de Chile
    • Predictive Analytics for Business with H2O in R: Coursera Project Network
    • Fundamentos de estadística aplicada: Universidad de los Andes

    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)

    Frequently Asked Questions about Random Forest

    Random forest is a classification algorithm that is a collection of various decision trees. It is a classification algorithm that, with the combination of trees, helps increase the overall results. Random forest is used for classification and regression tasks and shows how many uncorrelated pieces can produce more accurate predictions than the individual ones.‎

    Random forest is important to learn because it will help you advance in your data-related career. It will give you skills to perform more accurate tests and help you achieve results with a low prediction error. It is also important to learn random forest because it is widely used and helps you maintain the accuracy of large data even with missing variables. Learning random forest will save you time while providing better, more accurate results.‎

    Some typical careers that use random forest are data scientists and analytic jobs. In these careers, you will use random forest to analyze data and come up with predictions based on the results. The data gathered and analyzed can be from many different areas. This can include medical data to predict diseases or illnesses, market data to predict sales, or use data to predict the number of cars rented by season, for example. In an analytic job and as a data scientist you will use random forest to come up with accurate predictions.‎

    Online courses will help you learn about random forest because they will offer video lectures, readings, and examples to explain the material to you. These courses will give you the chance to practice and demonstrate your knowledge with various assignments or projects on different software. Online courses will also help you learn random forest by giving you the flexibility to study on your own time while having access to the material and experts that will guide you along the course.‎

    Online Random Forest courses offer a convenient and flexible way to enhance your knowledge or learn new Random Forest skills. Choose from a wide range of Random Forest courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Random Forest, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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