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Predict Diabetes with a Random Forest using R

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In this 1-hour long project-based course, you will learn how to (complete a training and test set using an R function, practice looking at data distribution using R and ggplot2, Apply a Random Forest model to the data, and examine the results using RMSE and a Confusion Matrix). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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Discover how to predict diabetes using the power of Random Forest algorithms in R with this engaging and hands-on course. Perfect for those passionate about Data Science & AI, this 1-hour project-based course guides you through essential steps such as completing a training and test set, examining data distribution with R and ggplot2, applying a Random Forest model, and evaluating your results with RMSE and a Confusion Matrix. Offered by Coursera, this intermediate-level course is designed for learners with some prior experience in data analysis and programming in R. The course content is delivered in a concise 240-minute format, making it ideal for those seeking to enhance their skills efficiently. Plus, with a free subscription option, this course is accessible to anyone eager to advance their knowledge in predictive modeling and machine learning. Join now and take a significant step towards mastering data-driven insights in the healthcare domain.