Data Science Workflow


Data Science Workflow

Training description

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.

Training agenda

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

Contact us about closed training

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