Principles, Statistical and Computational Tools for Reproducible Data Science
- 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.
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
- write a reproducible paper.
- Self-paced learning
- Video tutorials
- Recognised certification
- Modules : 7
- Hours : 3-8 Hours Per Week
- Level :Intermediate
- Price : Free