What is 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.

Why is random forest important to learn?

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.

What are typical careers that use random forest?

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.

How can online courses help me learn about random forest?

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.

What are the benefits of taking an online Random Forest 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.

What Random Forest courses are best for training and upskilling employees or the workforce?

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 .

Top Random Forest Courses - Learn Random Forest Online

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Explore the Random Forest Course Catalog

University of Colorado Boulder
Fundamentals of Macroscopic and Microscopic Thermodynamics
Skills you'll gain: Statistical Methods, Physics, Probability Distribution, Physical Science, Chemistry, Engineering Calculations, Calculus
4.3
Rating, 4.3 out of 5 stars
262 reviews
Advanced · Course · 1 - 4 Weeks
University of Minnesota
Introduction to Automated Analysis
Skills you'll gain: Test Automation, Regression Testing, Software Testing, Unit Testing, Test Tools, System Testing, Code Coverage, Security Testing, Verification And Validation, Test Case, Test Data, Debugging, Automation, Functional Requirement, Application Security
4.2
Rating, 4.2 out of 5 stars
82 reviews
Intermediate · Course · 1 - 4 Weeks
CertNexus
Build Regression, Classification, and Clustering Models
Skills you'll gain: Unsupervised Learning, Regression Analysis, Machine Learning Algorithms, Linear Algebra, Machine Learning, Predictive Modeling, Statistical Methods, Supervised Learning, Feature Engineering, Classification And Regression Tree (CART), Performance Tuning, Algorithms
4.4
Rating, 4.4 out of 5 stars
16 reviews
Intermediate · Course · 1 - 3 Months
Macquarie University
Create video, audio and infographics for online learning
Skills you'll gain: Video Production, Infographics, Multimedia, Peer Review, Content Creation, Constructive Feedback, Design Thinking, Media Production, Design, Storytelling, Scripting
4.8
Rating, 4.8 out of 5 stars
97 reviews
Beginner · Course · 1 - 3 Months
Arizona State University
Introduction to Machine Learning with Python
Skills you'll gain: Supervised Learning, Unsupervised Learning, Generative AI, Deep Learning, Image Analysis, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning, Artificial Neural Networks, Computer Vision, Computer Programming, Regression Analysis
3.7
Rating, 3.7 out of 5 stars
20 reviews
Beginner · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistical Inference for Estimation in Data Science
Skills you'll gain: Statistical Inference, Statistical Methods, Probability & Statistics, Statistical Modeling, Sampling (Statistics), Statistical Analysis, Data Science, Probability Distribution
4.1
Rating, 4.1 out of 5 stars
88 reviews
Intermediate · Course · 1 - 3 Months
University of Colorado Boulder
Statistical Inference and Hypothesis Testing in Data Science Applications
Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Data Ethics, Probability & Statistics, Statistical Inference, Statistical Analysis, Quantitative Research, Statistics, Probability Distribution
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
50 reviews
Intermediate · Course · 1 - 3 Months
University of Colorado Boulder
Data Analysis with Python Project
Skills you'll gain: Dimensionality Reduction, Data Analysis, Supervised Learning, Anomaly Detection, Machine Learning, Machine Learning Algorithms, Statistical Analysis, Unsupervised Learning, Data Mining, Analytics, Predictive Modeling, Regression Analysis, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Exploratory Data Analysis, Statistical Methods
5
Rating, 5 out of 5 stars
6 reviews
Intermediate · Course · 1 - 3 Months
Coursera Project Network
Diabetes Prediction With Pyspark MLLIB
Skills you'll gain: Data Cleansing, Apache Spark, PySpark, Data Manipulation, Applied Machine Learning, Data Processing, Classification And Regression Tree (CART), Predictive Modeling, Regression Analysis, Machine Learning, Google Cloud Platform
4.6
Rating, 4.6 out of 5 stars
22 reviews
Intermediate · Guided Project · Less Than 2 Hours
Johns Hopkins University
Tidyverse Skills for Data Science in R
Skills you'll gain: Tidyverse (R Package), Ggplot2, Data Wrangling, Statistical Modeling, Exploratory Data Analysis, Plot (Graphics), R Programming, Data Import/Export, Predictive Modeling, Statistical Visualization, Sampling (Statistics), Data Visualization Software, Statistical Hypothesis Testing, Data Analysis, Data Manipulation, Data Modeling, Web Scraping, Data Integration, Data Cleansing, Data Transformation
4.5
Rating, 4.5 out of 5 stars
104 reviews
Beginner · Specialization · 3 - 6 Months
Columbia University
Computational Methods in Pricing and Model Calibration
Skills you'll gain: Regression Analysis, Derivatives, Financial Market, Statistical Methods, Financial Modeling, Securities (Finance), Mathematical Modeling, Numerical Analysis, Equities, Financial Data, Python Programming, Probability Distribution, Algorithms
4.4
Rating, 4.4 out of 5 stars
40 reviews
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Mathematical Biostatistics Boot Camp 2
Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Statistical Methods, Probability & Statistics, Statistical Inference, Biostatistics, Sampling (Statistics), Data Analysis, Sample Size Determination, Risk Analysis, Probability Distribution
4.3
Rating, 4.3 out of 5 stars
133 reviews
Mixed · Course · 1 - 4 Weeks

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

Fundamentals of Macroscopic and Microscopic Thermodynamics: University of Colorado Boulder
Introduction to Automated Analysis: University of Minnesota
Build Regression, Classification, and Clustering Models: CertNexus
Create video, audio and infographics for online learning : Macquarie University
Introduction to Machine Learning with Python: Arizona State University
Statistical Inference for Estimation in Data Science: University of Colorado Boulder
Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
Data Analysis with Python Project : University of Colorado Boulder
Diabetes Prediction With Pyspark MLLIB: Coursera Project Network
Tidyverse Skills for Data Science in R: Johns Hopkins University

Random Forest Courses Online