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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

    • 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

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Bayesian Statistics: From Concept to Data Analysis

      Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • 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

    • C

      Coursera Project Network

      Support Vector Machines in Python, From Start to Finish

      Skills you'll gain: Scikit Learn (Machine Learning Library), Tensorflow, Cloud Computing, Classification And Regression Tree (CART), Supervised Learning, Applied Machine Learning, Machine Learning Methods, Pandas (Python Package), Data Visualization, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      155 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      N

      New York Institute of Finance

      Introduction to Risk Management

      Skills you'll gain: Risk Management, Business Risk Management, Risk Modeling, Operational Risk, Enterprise Risk Management (ERM), Credit Risk, Risk Analysis, Portfolio Management, Capital Markets, Financial Market, Financial Regulation, Financial Modeling, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      702 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Operations Analytics

      Skills you'll gain: Business Analytics, Descriptive Analytics, Predictive Analytics, Analytics, Demand Planning, Data-Driven Decision-Making, Operational Analysis, Business Operations, Risk Analysis, Forecasting, Operations Management, Simulation and Simulation Software, Process Optimization, Decision Making, Decision Tree Learning, Spreadsheet Software, Microsoft Excel, Probability Distribution

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · 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

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Linear Algebra, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    • N

      Northwestern University

      Fundamentals of Digital Image and Video Processing

      Skills you'll gain: Image Analysis, Digital Communications, Computer Vision, Data Processing, Visualization (Computer Graphics), Medical Imaging, Electrical and Computer Engineering, Motion Graphics, Linear Algebra, Color Theory, Bayesian Statistics, Applied Mathematics, Sampling (Statistics), Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • 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
      ·
      302 reviews

      Intermediate · Guided Project · Less Than 2 Hours

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

    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Scalable Machine Learning on Big Data using Apache Spark: IBM
    • Support Vector Machines in Python, From Start to Finish: Coursera Project Network
    • Introduction to Risk Management: New York Institute of Finance
    • Operations Analytics: University of Pennsylvania
    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Fundamentals of Engineering Exam Review: Georgia Institute of Technology
    • Machine Learning: Regression: University of Washington

    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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