Introduction to Data Science Methods in Python and R

An increasing mandate for many HR functions worldwide is to adopt tools for processing and analyzing workforce data quickly, efficiently, reproducibly, and at scale. This course provides the necessary foundation for collecting, manipulating, visualizing, and analyzing common HR data sources — principally in the Python programming language (pandas, seaborn, statsmodels), with a final unit introducing R as a second language. Learn how to write code to handle common HR reporting tasks, clean and combine data from HRIS systems and employee surveys, test for meaningful differences between groups, build and interpret statistical models of outcomes like compensation and attrition, and communicate results to decision-makers — all in an automated and reproducible manner.
Continuing Education Units (CEU) : 1

You'll walk away with

• Understand the fundamentals of the Python programming language for data collection, processing, visualization, analysis, and statistical modeling — and translate that foundation into working R code.
• Demonstrate foundational ability to load, transform, analyze, visualize, and export data common to HR analytics and reporting projects — including data from HRIS systems and employee surveys — and communicate the results to non-technical audiences.

Ideal for

• Those interested in how people analytics affects business decisions
• HR professionals who are seeking to broaden their data analytics skills