THE PROJECT’S SUCCESS
Data Science Workflow
This training presents techniques for running reproducible Data Science projects in an effective manner. The training covers project management, working in analytical group and methods of presentation the results to the users.
Duration: 2 days 8 hours each (including an hour lunch break)
Requirements: knowledge of R programming language at an intermediate level which can be acquired during our training “Introduction to R.”
Part one: Ready, steady, …
- Types of projects
- Methods of project management
Part two: Control yourself!
- Git – the basic syntax
- Managing branches
- Eliminating conflicts
- The best practices
Part three: Repeatability is crucial
- R tools overview – projectTemplate
- R tools overview – remake
- packrat – problem of versioning R packages
Part four: Show off your work by publishing it!
- Creating complex reporting tools with R Markdown package
- Publishing the results with R Markdown
- Creating PowerPoint presentations with R
- Publishing the results with shiny
- Building autonomic environments with Docker
Upcoming open trainings
Currently, no open training covering the given issue is planned. We encourage you to contact us regarding the closed training.
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