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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

    • Status: New
      New
      Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistics and Applied Data Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Statistical Programming, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      33 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      Universitat Autònoma de Barcelona

      Detección de objetos

      Skills you'll gain: Computer Vision, Image Analysis, Classification And Regression Tree (CART), Machine Learning Algorithms, Supervised Learning, Machine Learning, Deep Learning, Feature Engineering, Artificial Neural Networks, Histogram

      4.4
      Rating, 4.4 out of 5 stars
      ·
      352 reviews

      Mixed · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Diabetes Prediction With Pyspark MLLIB

      Skills you'll gain: Data Cleansing, Apache Spark, PySpark, Data Manipulation, Applied Machine Learning, Data Processing, Classification And Regression Tree (CART), Predictive Modeling, Regression Analysis, Machine Learning, Google Cloud Platform

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Carnegie Mellon University

      Statistical Thermodynamics: Molecules to Machines

      Skills you'll gain: Mechanical Engineering, Chemical Engineering, Engineering, Chemical and Biomedical Engineering, Applied Mathematics, Chemistry, Biochemistry, Engineering Analysis, Physics, Molecular, Cellular, and Microbiology, Mathematical Modeling, Physical Science, Probability Distribution

      3.9
      Rating, 3.9 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      É

      École normale supérieure

      Statistical Mechanics: Algorithms and Computations

      Skills you'll gain: Sampling (Statistics), Physics, Simulations, Statistical Programming, Computational Logic, Numerical Analysis, Markov Model, Mechanics, Quantitative Research, Algorithms, Programming Principles, Applied Mathematics, Linear Algebra, Integral Calculus

      4.8
      Rating, 4.8 out of 5 stars
      ·
      264 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Macquarie University

      Create video, audio and infographics for online learning

      Skills you'll gain: Video Production, Infographics, Multimedia, Content Creation, Constructive Feedback, Design Thinking, Design, Graphic and Visual Design, Storytelling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      97 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Supply Chain Optimization

      Skills you'll gain: Supply Chain Planning, Supply Chain Management, Inventory Management System, Process Optimization, Operations Management, Demand Planning, Resource Allocation, Capacity Management, Microsoft Excel, Cost Reduction, Simulation and Simulation Software, Mathematical Modeling, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      40 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Michigan State University

      Forest Carbon Credits and Initiatives

      Skills you'll gain: Project Design, Sustainability Reporting, Project Finance, Verification And Validation, Project Scoping, Environment and Resource Management, Continuous Monitoring, Feasibility Studies, Cost Benefit Analysis, Market Analysis, Estimation, Corporate Sustainability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      29 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Mind and Machine

      Skills you'll gain: Problem Solving, Computational Thinking, Computer Vision, Game Theory, Image Analysis, Artificial Neural Networks, Probability Distribution, Behavioral Economics, Logical Reasoning, Algorithms, Human Development, Analytical Skills, Artificial Intelligence and Machine Learning (AI/ML), Computer Graphics, Artificial Intelligence, Psychology, Human Learning, Human Factors, Theoretical Computer Science, Human Machine Interfaces

      4.4
      Rating, 4.4 out of 5 stars
      ·
      360 reviews

      Beginner · Specialization · 3 - 6 Months

    • E

      EIT Digital

      Quantitative Model Checking

      Skills you'll gain: Computational Logic, Markov Model, Verification And Validation, Theoretical Computer Science, Mathematical Modeling, Systems Analysis, Probability, Algorithms, Real-Time Operating Systems, Probability Distribution

      4.2
      Rating, 4.2 out of 5 stars
      ·
      53 reviews

      Intermediate · Course · 1 - 3 Months

    • N

      National Taiwan University

      頑想學概率:機率一 (Probability (1))

      Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Data Literacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      364 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of London

      Statistics for International Business

      Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Data Presentation, Statistics, Estimation, Probability, Data-Driven Decision-Making, Probability & Statistics, Statistical Inference, Statistical Hypothesis Testing, Probability Distribution, Data Visualization, Data Analysis, Histogram, Graphing

      3.8
      Rating, 3.8 out of 5 stars
      ·
      308 reviews

      Mixed · Course · 1 - 4 Weeks

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

    • Statistics and Applied Data Analysis: University of Colorado Boulder
    • Detección de objetos: Universitat Autònoma de Barcelona
    • Diabetes Prediction With Pyspark MLLIB: Coursera Project Network
    • Statistical Thermodynamics: Molecules to Machines: Carnegie Mellon University
    • Statistical Mechanics: Algorithms and Computations: École normale supérieure
    • Create video, audio and infographics for online learning : Macquarie University
    • Supply Chain Optimization: University of California, Irvine
    • Forest Carbon Credits and Initiatives: Michigan State University
    • Mind and Machine: University of Colorado Boulder
    • Quantitative Model Checking: EIT Digital

    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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