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

Explore the Random Forest Course Catalog

University of Colorado Boulder
Data Acquisition, Risk, and Estimation
Skills you'll gain: Sampling (Statistics), Engineering Management, Estimation, Sample Size Determination, Statistical Methods, Leadership and Management, Statistical Software, Leadership, Data Analysis, Data-Driven Decision-Making, Statistical Analysis, Statistical Hypothesis Testing, Risk Analysis, Probability & Statistics, R Programming, Business Risk Management, Return On Investment
Intermediate · Course · 1 - 3 Months
SkillUp EdTech
Advanced Statistical Analysis and Tools
Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Process Improvement, Lean Methodologies, Kaizen Methodology, Lean Six Sigma, Process Capability, Six Sigma Methodology, Risk Analysis, Quality Improvement, Process Analysis, Statistical Analysis, Statistical Methods, Continuous Improvement Process, Quality Assessment, Risk Management, Business Process, Sampling (Statistics), Statistical Inference, Data Collection
Intermediate · Course · 1 - 4 Weeks
Johns Hopkins University
Emerging Approaches for Measuring Population Health
Skills you'll gain: Survey Creation, Sampling (Statistics), Data Collection, Epidemiology, Health Assessment, Program Evaluation, Research Methodologies, Health Systems, Health Information Management and Medical Records, Data Quality, Data Integration, Diversity Awareness
Beginner · Course · 1 - 4 Weeks
Status: Free
Ball State University
Statistical Methods for Data Science
Skills you'll gain: Probability, Probability Distribution, Statistical Methods, Statistical Inference, Bayesian Statistics, Statistical Analysis, Statistical Modeling, R Programming, Statistical Hypothesis Testing, Sampling (Statistics), Dimensionality Reduction, Statistical Visualization
Build toward a degree
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Data Science Decisions in Time: Using Data Effectively
Skills you'll gain: Reinforcement Learning, Data-Driven Decision-Making, Markov Model, Time Series Analysis and Forecasting, Bayesian Statistics, Data Science, Predictive Analytics, Statistical Methods, Anomaly Detection, Machine Learning Methods, Statistical Analysis, Sampling (Statistics)
Intermediate · Course · 1 - 3 Months
Fundação Instituto de Administração
Pesquisa de Mercado com Métodos Quantitativos
Skills you'll gain: Quantitative Research, Survey Creation, Sampling (Statistics), Data Collection, Market Research, Data Analysis, Statistical Analysis, Data Quality, Sample Size Determination, Consumer Behaviour
Beginner · Course · 1 - 4 Weeks
Status: Free
University of Maryland, College Park
Cómo manejar datos faltantes
Skills you'll gain: Sampling (Statistics), Data Cleansing, Data Quality, Stata, Statistical Analysis, Statistical Software, Statistical Methods, Data Analysis, Regression Analysis, Data Integrity, R Programming, Probability & Statistics
Mixed · Course · 1 - 3 Months
American Psychological Association
Basic Inferential Statistics for Psychology
Skills you'll gain: Sample Size Determination, Statistical Hypothesis Testing, Probability & Statistics, Statistical Methods, Probability Distribution, Statistical Reporting, Quantitative Research, Statistical Analysis, Statistical Software, Statistical Inference, Sampling (Statistics), Data Analysis, Descriptive Statistics, Experimentation, Probability, Statistics, Psychology
Beginner · Specialization · 3 - 6 Months
Packt
ReactJS - The Beginner Masterclass
Skills you'll gain: React.js, Application Deployment, Bootstrap (Front-End Framework), Application Development, Javascript, UI Components, Front-End Web Development, Development Environment, Cascading Style Sheets (CSS), JSON, User Interface (UI), GitHub, Application Programming Interface (API)
Beginner · Course · 1 - 3 Months
DeepLearning.AI
Applied Statistics for Data Analytics
Skills you'll gain: Statistical Hypothesis Testing, Statistics, Probability Distribution, Statistical Analysis, Probability & Statistics, Data Analysis, Sampling (Statistics), Statistical Inference, Descriptive Statistics, Probability, Correlation Analysis, Exploratory Data Analysis, Generative AI
Beginner · Course · 1 - 4 Weeks
Status: Free
Ball State University
Introduction to Data Science
Skills you'll gain: Data Ethics, Data Collection, Data Visualization, Probability & Statistics, R Programming, Data Science, Sampling (Statistics), Database Software, Simulations, Data Wrangling, Analytical Skills, Mathematical Theory & Analysis, Statistical Analysis, Regression Analysis, Data Manipulation, Data Structures
Build toward a degree
Beginner · Course · 3 - 6 Months
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, Statistical Analysis, Sampling (Statistics)
Beginner · Course · 1 - 3 Months