Principles, Statistical and Computational Tools for Reproducible Data Science
About Course
Today the principles and techniques of reproducible research are more important than ever, across diverse disciplines from astrophysics to political science. No one wants to do research that can’t be reproduced. Thus, this course is really for anyone who is doing any data intensive research. While many of us come from a biomedical background, this course is for a broad audience of data scientists.
Requirements
Knowledge of Statistics Data Analysis
What I will learn?
Fundamental of reproducible science
Key elements of data provenance
Reproducible experimental design
Reproducible data analysis using statistical methods
Computational and statistical tools
Understand analysis paradigms, a series of concepts
Learn version control and reproducible dynamic report generation
Understand workflows and thought patterns
Learn new methods and tools for reporting & reproducible research
