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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

      Data Analysis Using Pyspark

      Skills you'll gain: PySpark, Matplotlib, Apache Spark, Big Data, Data Processing, Distributed Computing, Data Visualization, Data Analysis, Data Manipulation, Query Languages, Google Cloud Platform

      4.5
      Rating, 4.5 out of 5 stars
      ·
      301 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • U

      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

      Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Statistics, Bayesian Statistics, Data Science, Statistical Analysis, Statistical Inference

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      252 reviews

      Intermediate · Course · 1 - 3 Months

    • E

      EDHEC Business School

      Introduction to Portfolio Construction and Analysis with Python

      Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Risk Analysis, Financial Modeling, Risk Management, Financial Analysis, NumPy, Probability Distribution, Python Programming, Simulations, Pandas (Python Package), Matplotlib, Data Manipulation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • N

      New York University

      Guided Tour of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Financial Services, Finance, Tensorflow, Jupyter, Reinforcement Learning

      3.8
      Rating, 3.8 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Georgia Institute of Technology

      Fundamentals of Engineering Exam Review

      Skills you'll gain: Structural Analysis, Probability & Statistics, Structural Engineering, Hydraulics, Statistical Methods, Statistics, Engineering Analysis, Mechanical Engineering, Probability, Engineering, Probability Distribution, Mechanics, Engineering Calculations, Civil Engineering, Applied Mathematics, Algebra, Advanced Mathematics, Calculus, Differential Equations, Geometry

      4.6
      Rating, 4.6 out of 5 stars
      ·
      611 reviews

      Mixed · Course · 1 - 3 Months

    • I

      IBM

      Scalable Machine Learning on Big Data using Apache Spark

      Skills you'll gain: Apache Spark, PySpark, Applied Machine Learning, Big Data, Machine Learning Methods, Data Storage, Data Pipelines, Machine Learning Algorithms, Distributed Computing, Data Processing, Exploratory Data Analysis, Statistical Analysis

      3.8
      Rating, 3.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Amsterdam

      Basic Statistics

      Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Sampling (Statistics), Probability Distribution, Correlation Analysis, Probability, Statistical Inference, Regression Analysis, Sample Size Determination, Statistics, Scientific Methods

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

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of London

      Get Interactive: Practical Teaching with Technology

      Skills you'll gain: Education Software and Technology, Learning Management Systems, Collaborative Software, Test Tools, Content Management Systems, Security Software, Video Production

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • W

      Wesleyan University

      Machine Learning for Data Analysis

      Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Predictive Modeling, Random Forest Algorithm, Applied Machine Learning, Predictive Analytics, Unsupervised Learning, Machine Learning, Supervised Learning, Data Analysis, Data Mining, Feature Engineering, Exploratory Data Analysis, Regression Analysis, Statistical Analysis, Statistical Methods

      4.2
      Rating, 4.2 out of 5 stars
      ·
      324 reviews

      Mixed · Course · 1 - 4 Weeks

    • K

      Kennesaw State University

      Six Sigma Tools for Analyze

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Process Analysis, Probability Distribution, Process Capability, Statistical Process Controls, Lean Methodologies, Probability & Statistics, Process Improvement, Quality Improvement, Process Mapping, Statistical Analysis, Systems Of Measurement, Risk Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Detecting COVID-19 with Chest X-Ray using PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Machine Learning Methods, Medical Imaging, Computer Vision, X-Ray Computed Tomography

      4.5
      Rating, 4.5 out of 5 stars
      ·
      337 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Statistical Inference, Statistical Methods, Pandas (Python Package), Probability & Statistics, Risk Analysis, Financial Trading, Financial Data, Data Manipulation, Statistical Analysis, Regression Analysis, Financial Analysis, Jupyter, Financial Modeling

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.5K reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Data Analysis Using Pyspark: Coursera Project Network
    • Probability Theory: Foundation for Data Science: University of Colorado Boulder
    • Introduction to Portfolio Construction and Analysis with Python: EDHEC Business School
    • Guided Tour of Machine Learning in Finance: New York University
    • Fundamentals of Engineering Exam Review: Georgia Institute of Technology
    • Scalable Machine Learning on Big Data using Apache Spark: IBM
    • Basic Statistics: University of Amsterdam
    • Get Interactive: Practical Teaching with Technology: University of London
    • Machine Learning for Data Analysis: Wesleyan University
    • Six Sigma Tools for Analyze: Kennesaw State University

    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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