Get yourself trained on R: Data Visualization with this Online Training R: Data Visualization with R – A Complete Guide!: 3-in-1.
Online Training R: Data Visualization with R – A Complete Guide!: 3-in-1
Effective visualization helps you get better insights from your data, make better and more informed business decisions! R is one of the most widely used open source languages for data and graph analysis. It is platform-independent and allows users to load various packages as well as develop their own packages to interpret data better. R gives aspiring analysts and data scientists the ability to represent complex sets of data in an impressive way. So, if you’re a data science professional and want to learn about the powerful data visualization techniques of R, then go for this Learning Path.This comprehensive 3-in-1 course follows a practical approach, where each recipe presents unique functions of plots, charts, and maps as well as visualization of 2D and 3D interactive plots in a step-by-step manner! Youll begin with generating various plots in R using the basic R plotting techniques. Utilize R packages to add context and meaning to your data. Finally, you’ll design interactive visualizations and integrate them on your website or blog!By the end of the course, youll master the visualization capabilities of R to build interactive graphs, plots, and Pie charts as well as visualize 2D and 3D interactive plots.Contents and OverviewThis training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Learning R for Data Visualization, covers getting to grips with Rs most popular packages and functions to create interactive visualizations for the web. We start by importing data in R from popular formats such as CSV and Excel tables. Then you will learn how to create basic plots such as histograms, scatterplots, and more, with the default options, which guarantees stunning results. In the final part of the course, the Shiny package will be extensively discussed. This allows you to create fully-featured web pages directly from the R console, and Shiny also allows it to be uploaded to a live website where your peers and colleagues can browse it and you can share your work. You will see how to build a complete website to import and plot data, plus we will present a method to upload it for everybody to use. Finally, you will revise all the concepts you’ve learned while having some fun creating a complete website. By the end of the course, you will have an armor full of different visualization techniques, with the capacity to apply these abilities to real-world data sets.The second course, R Data Visualization – Basic Plots, Maps, and Pie Charts, covers mastering the visualization capabilities of R to build interactive graphs, plots, and Pie. We start – off with the basics of R plots and an introduction to heat maps and customizing them. After this, we gradually take you through creating interactive maps using the googleVis package. Finally, we generate choropleth maps and contouring maps, bubble plots, and pie charts.The third course, R Data Visualization – Word Clouds and 3D Plots, covers advanced visualization techniques in R to build word clouds, 3D plots, and more. We start off with the basics of R plots and an introduction to heat maps and customizing them. After this, we gradually take you through creating interactive maps using the googleVis package. Finally, we generate choropleth maps and contouring maps, bubble plots, and pie charts.By the end of the course, youll master the visualization capabilities of R to build interactive graphs, plots, and Pie charts as well as visualize 2D and 3D interactive plots. About the AuthorsFabio Veronesi obtained a Ph.D. in digital soil mapping from Cranfield University and then moved to ETH Zurich, where he has been working for the past three years as a postdoc. In his career, Dr. Veronesi worked at several topics related to environmental research: digital soil mapping, cartography, and shaded relief, renewable energy and transmission line siting. During this time Dr. Veronesi specialized in the application of spatial statistical techniques to environmental data.Atmajit Singh Gohil works as a senior consultant at a consultancy firm in New York City. After graduating, he worked in the financial industry as a Fixed Income Analyst. He writes about data manipulation, data exploration, visualization, and basic R plotting functions on his blog. He has a master’s degree in financial economics from the State University of New York (SUNY), Buffalo. He also graduated with a Master of Arts degree in economics from the University of Pune, India. He loves to read blogs on data visualization and loves to go out on hikes in his free time.
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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.