Transform your coding from quick fixes to lasting solutions—learn to build robust, professional systems that serve as long-term research assets and communicate clearly to collaborators and your future self.

This hands-on workshop teaches essential practices for writing reproducible, professional-grade code that grows with your research career. You'll discover how to apply computational "compassion" and legibility principles, designing code that minimizes burden on others while maximizing readability and navigability of your research process.

Attendees will learn how to:

• Organize research projects using structured protocols and effective naming conventions
• Write clear, maintainable code through comprehensive documentation, logical flow, and meaningful variable names
• Implement control files that orchestrate complex workflows and automate error handling
• Create publication-ready visualizations and tables that emphasize statistical substance
• Apply proactive debugging strategies and transform disposable scripts into reusable systems

Audience: Intermediate R/Python/Stata users with basic familiarity with at least one statistical programming language

Registration: In person, RKZ Library Classroom 01