: Using R to determine if the differences between proportions are statistically meaningful. 3. Predictive Modeling and Regression
The heart of data science lies in prediction. This course introduces learners to several Data Modeling Online Training Courses concepts that form the backbone of machine learning.
: Establishing baseline statistics like means, medians, and standard deviations.
is a popular intermediate-level course on LinkedIn Learning taught by data scientist Barton Poulson. The course focuses on using the R programming language to move beyond basic data visualization and into advanced statistical modeling and predictive analytics. Course Overview and Structure
Welcome to , the second installment in LinkedIn’s comprehensive R programming series. If Part 1 introduced you to the grammar of R—vectors, data frames, and the Tidyverse—Part 2 is where you learn to make R think .
: Specialized tools for predicting specific points in a distribution or count-based data. 4. Clustering and Classification
