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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

    • U

      University of Michigan

      Muestreo de personas, redes y registros

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Data Collection, Surveys, Statistical Methods, Quantitative Research, Statistics, Probability & Statistics, Research Design, Statistical Software, Network Analysis

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      ReactJS - The Beginner Masterclass

      Skills you'll gain: React.js, Application Deployment, Web Applications, Javascript, Bootstrap (Front-End Framework), JavaScript Frameworks, Development Environment, User Interface (UI), Cascading Style Sheets (CSS), Application Programming Interface (API), GitHub

      Beginner · Course · 1 - 3 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Geographical Information Systems - Part 2

      Skills you'll gain: Spatial Analysis, Spatial Data Analysis, GIS Software, Geographic Information Systems, Geospatial Mapping, Geostatistics, Interactive Data Visualization, Data Integration, Data Mapping, Augmented Reality, Sampling (Statistics)

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      M

      Macquarie University

      Excel Skills for Statistics and Data Analysis: Intermediate

      Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Statistical Inference, Microsoft Excel, Correlation Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Regression Analysis, Data Analysis, Sampling (Statistics), Descriptive Statistics, Forecasting

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Data Processing and Manipulation

      Skills you'll gain: Pivot Tables And Charts, Data Manipulation, Data Transformation, Data Processing, Data Warehousing, Data Cleansing, Dimensionality Reduction, Data Quality, Anomaly Detection, Feature Engineering, Sampling (Statistics), Exploratory Data Analysis, Statistical Methods

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Instructor Network

      OpenAI: Consistent Response Strategies

      Skills you'll gain: Prompt Engineering, OpenAI, Large Language Modeling, Generative AI, Technical Communication, Sampling (Statistics), Natural Language Processing, Performance Tuning

      5
      Rating, 5 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Preparing and Aggregating Data for Visualizations using Cloud Dataprep

      Skills you'll gain: Data Visualization Software, Data Wrangling, Data Manipulation, Data Import/Export, Data Transformation, Data Cleansing, Extract, Transform, Load, Sampling (Statistics)

      Beginner · Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Analysis and Interpretation of Large-Scale Programs

      Skills you'll gain: Program Evaluation, Health Equity, Quantitative Research, Data Analysis, Statistical Analysis, Analysis, Statistical Reporting, Data Collection, Sampling (Statistics), Public Health and Disease Prevention, Maternal Health, Data Quality, Research Design

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Household Surveys for Program Evaluation in LMICs

      Skills you'll gain: Surveys, Survey Creation, Sampling (Statistics), Program Evaluation, Data Management, Data Collection, Data Analysis, Data Cleansing, Data Quality, Research Design, Sample Size Determination, Interviewing Skills, Data Presentation, Data Ethics

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Advanced Probability and Statistical Methods

      Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Probability & Statistics, Statistical Methods, Probability Distribution, Data Analysis, Markov Model, Data Science, Statistical Modeling, Statistics, Statistical Inference, Probability, R Programming, Applied Mathematics

      Intermediate · Course · 1 - 3 Months

    • U

      University of Maryland, College Park

      Cómo combinar y analizar datos complejos

      Skills you'll gain: Data Integration, Data Synthesis, Data Ethics, R Programming, Statistical Software, Analytical Skills, Data Analysis Software, Statistical Methods, Statistical Programming, Statistical Analysis, Sampling (Statistics), Regression Analysis, Statistical Modeling, Probability & Statistics, Descriptive Statistics, Information Privacy

      Mixed · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Machine/Deep Learning for Mining Quality Prediction-Enhanced

      Skills you'll gain: Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Applied Machine Learning, Data Manipulation, Data Analysis, Random Forest Algorithm, Decision Tree Learning, Machine Learning Algorithms, Data Visualization Software, Artificial Neural Networks, Deep Learning, Statistical Methods

      Beginner · Guided Project · Less Than 2 Hours

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

    • Muestreo de personas, redes y registros: University of Michigan
    • ReactJS - The Beginner Masterclass: Packt
    • Geographical Information Systems - Part 2: École Polytechnique Fédérale de Lausanne
    • Excel Skills for Statistics and Data Analysis: Intermediate: Macquarie University
    • Data Processing and Manipulation: University of Colorado Boulder
    • OpenAI: Consistent Response Strategies: Coursera Instructor Network
    • Preparing and Aggregating Data for Visualizations using Cloud Dataprep: Google Cloud
    • Analysis and Interpretation of Large-Scale Programs: Johns Hopkins University
    • Household Surveys for Program Evaluation in LMICs: Johns Hopkins University
    • Advanced Probability and Statistical Methods: Johns Hopkins 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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