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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

    • D

      Duke University

      Mastering Data Analysis in Excel

      Skills you'll gain: Microsoft Excel, Probability Distribution, Business Risk Management, Predictive Modeling, Regression Analysis, Risk Modeling, Business Analytics, Statistical Methods, Forecasting, Data Analysis, Probability, Financial Modeling, Classification And Regression Tree (CART)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.9K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of California San Diego

      Machine Learning With Big Data

      Skills you'll gain: Exploratory Data Analysis, Apache Spark, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Data Transformation, Predictive Modeling, Data Cleansing, Supervised Learning, Decision Tree Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.5K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Amsterdam

      Quantitative Methods

      Skills you'll gain: Scientific Methods, Research Design, Sampling (Statistics), Science and Research, Research, Research Methodologies, Surveys, Quantitative Research, Social Sciences, Experimentation, Ethical Standards And Conduct

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.3K reviews

      Mixed · Course · 1 - 3 Months

    • D

      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Principal Component Analysis with NumPy

      Skills you'll gain: Exploratory Data Analysis, NumPy, Data Visualization, Data Analysis, Seaborn, Matplotlib, Cloud Computing, Jupyter, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Python Programming, Linear Algebra

      4.6
      Rating, 4.6 out of 5 stars
      ·
      295 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      S

      Stanford University

      Social and Economic Networks: Models and Analysis

      Skills you'll gain: Network Analysis, Network Model, Social Sciences, Sociology, Economics, Policy, and Social Studies, Game Theory, Behavioral Economics, Graph Theory, Mathematical Modeling, Markov Model, Probability & Statistics, Probability Distribution, Bayesian Statistics, Simulations

      4.8
      Rating, 4.8 out of 5 stars
      ·
      754 reviews

      Advanced · Course · 1 - 3 Months

    • 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
      ·
      862 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Research Proposal: Initiating Research

      Skills you'll gain: Market Research, Proposal Writing, Research Methodologies, Market Analysis, Business Research, Data Collection, Quantitative Research, Business Writing, Sampling (Statistics), Survey Creation, Qualitative Research, Request for Proposal, Client Services, Professional Networking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      918 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Data Science Ethics

      Skills you'll gain: Data Ethics, Data Sharing, Information Privacy, General Data Protection Regulation (GDPR), Personally Identifiable Information, Data Security, Data Governance, Ethical Standards And Conduct, Big Data, Intellectual Property, Data Analysis, Social Sciences, Sampling (Statistics), Data-Driven Decision-Making, Diversity Awareness

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.2K reviews

      Beginner · Course · 1 - 3 Months

    • 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

    • U

      University of Alberta

      Sample-based Learning Methods

      Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • R

      Rice University

      Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

      Skills you'll gain: Descriptive Statistics, Probability & Statistics, Probability Distribution, Business Analytics, Microsoft Excel, Data Analysis, Statistical Analysis, Box Plots, Sampling (Statistics), Correlation Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.6K reviews

      Mixed · Course · 1 - 4 Weeks

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    1…8910…33

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

    • Mastering Data Analysis in Excel: Duke University
    • Machine Learning With Big Data: University of California San Diego
    • Quantitative Methods: University of Amsterdam
    • Introduction to Probability and Data with R: Duke University
    • Principal Component Analysis with NumPy: Coursera Project Network
    • Social and Economic Networks: Models and Analysis: Stanford University
    • Combinatorics and Probability: University of California San Diego
    • Research Proposal: Initiating Research: University of California, Davis
    • Data Science Ethics: University of Michigan
    • Operations Analytics: University of Pennsylvania

    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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