Linkedin R Essential Training Part 2: Modeling Data _top_ Jun 2026

Before building complex models, you must understand the underlying structure of your information. This course emphasizes "minimalism in data work," focusing on getting the most insight from the simplest methods.

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 . linkedin r essential training part 2: modeling data

Data modeling is the process of creating a visual representation of data structures, relationships, and constraints to ensure data consistency, integrity, and scalability. It involves identifying entities, attributes, and relationships between them to create a framework for data storage, retrieval, and analysis. Effective data modeling is essential for businesses to make informed decisions, improve data quality, and reduce data redundancy. Before building complex models, you must understand the

After mastering modeling, proceed to to learn: If Part 1 introduced you to the grammar

: Using k-means and hierarchical clustering to group similar cases together.