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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: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Machine Learning: Theory and Hands-on Practice with Python

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Deep Learning, Machine Learning Algorithms, Dimensionality Reduction, Applied Machine Learning, Decision Tree Learning, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Predictive Modeling, Classification And Regression Tree (CART), Python Programming, Computer Vision, Image Analysis, Mathematical Modeling, Artificial Neural Networks, Machine Learning, Data Science

      Build toward a degree

      3.5
      Rating, 3.5 out of 5 stars
      ·
      113 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      A

      Arizona State University

      Design of Experiments

      Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Design Strategies, Probability & Statistics, Data Analysis, Mathematical Modeling, Data Transformation, Descriptive Statistics, Probability Distribution, Statistical Hypothesis Testing, Variance Analysis, Quality Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      360 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      É

      École Polytechnique Fédérale de Lausanne

      Functional Program Design in Scala

      Skills you'll gain: Scala Programming, Software Design, Software Design Patterns, Functional Design, Event-Driven Programming, Java, Programming Principles, Performance Tuning, Data Structures, Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Mathematical Biostatistics Boot Camp 1

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

      4.4
      Rating, 4.4 out of 5 stars
      ·
      514 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Combinatorics and Probability

      Skills you'll gain: Combinatorics, Probability, Algorithms, Mathematical Modeling, Computational Thinking, Statistics, Game Theory, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      863 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Design Thinking and Predictive Analytics for Data Products

      Skills you'll gain: Supervised Learning, Feature Engineering, Predictive Modeling, Data Manipulation, Applied Machine Learning, Design Thinking, Advanced Analytics, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), Data Science, Data Cleansing, Classification And Regression Tree (CART), Regression Analysis, Data Processing, Tensorflow, Statistical Methods

      4.5
      Rating, 4.5 out of 5 stars
      ·
      65 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Machine Learning: Clustering & Retrieval

      Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Text Mining, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Probability Distribution, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Amsterdam

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sampling (Statistics), Probability & Statistics, Regression Analysis, Statistical Inference, Statistical Analysis, Quantitative Research, Probability Distribution, R Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      599 reviews

      Mixed · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Classification Trees in Python, From Start To Finish

      Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Data Transformation, Supervised Learning, Predictive Modeling, Feature Engineering, Scikit Learn (Machine Learning Library), Data Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      230 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Business Applications of Hypothesis Testing and Confidence Interval Estimation

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sample Size Determination, Statistical Inference, Estimation, Statistics, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Microsoft Excel, Excel Formulas, Decision Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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, Statistical Machine Learning, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Machine Learning, Data Analysis, Random Forest Algorithm

      4.8
      Rating, 4.8 out of 5 stars
      ·
      24 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Optimizing Machine Learning Performance: Alberta Machine Intelligence Institute
    • Machine Learning: Theory and Hands-on Practice with Python: University of Colorado Boulder
    • Design of Experiments: Arizona State University
    • Functional Program Design in Scala: École Polytechnique Fédérale de Lausanne
    • Mathematical Biostatistics Boot Camp 1: Johns Hopkins University
    • Combinatorics and Probability: University of California San Diego
    • Design Thinking and Predictive Analytics for Data Products: University of California San Diego
    • Machine Learning: Clustering & Retrieval: University of Washington
    • Inferential Statistics: University of Amsterdam
    • Classification Trees in Python, From Start To Finish: Coursera Project Network

    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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