Get yourself trained on Docker Containers for with this Online Training Docker Containers for Data Science and Reproducible Research.
Online Training Docker Containers for Data Science and Reproducible Research
Get excited!This course is designed to quickly start using Docker Containers for Data Science and Reproducible Research by reproducing several practical examples. Course will help to setup Docker Environment on your machine (Mac, Windows, …). Course will proceed with all steps to create custom and distributed development environment [RStudio] in a container. Work as usual add or develop the research document into your Container, test it and distribute in an image! Result will be reproducible independently on the R version of other persons, perhaps after several years…Same ideas will be provided to just run R programs in the container. We will demonstrate this capability including testing the container on completely different machines (Mac and Windows)Summary of ideas we will cover in this course:Reproduce and share work on a different infrastructureBe able to repeat the work after several yearsUse R-Studio in an isolated environmentTips to personalize work with Docker including usage of Automated BuildsWhat is covered by this course?This course will provide several use cases on using Docker Containers for Data Science:Preparing your computer for using DockerWorking pipeline to develop docker imageBuilding Docker image to work with R-Studio in Interactive modeBuilding Docker images to run R programsMore relevant materials may be added to this courseWhy to take this course and not other?Added value of this course is to provide a quick overview of functionality and to provide valuable methods and templates to build on. Focus of this course is to make a learning journey as easy as possible – simply watch these videos and reuse provided code!Just Start using Docker Containers with your Data Science tools by reproducing this course!
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.