2 new Courses!

We just launched Building Web Applications in R with Shiny: Case Studies and Cluster Analysis in R! The Shiny case studies will teach you how to develop Shiny apps, the cluster analysis in R courses will cover two clustering methods. [DataCamp]( New Courses! [ ]( [Play Now]( [ ]( Building Web Applications in R with Shiny: Case Studies Dean Attali, Founder & Lead R-Shiny Consultant at AttaliTech Ltd After learning the basics of using Shiny to build web applications, this course will take you to the next level by putting your newly acquired skills into use. You'll get experience developing fun and realistic Shiny apps to explore a dataset, to generate a customized plot, and even to create a wordcloud. [Start Learning]( [Cluster Analysis in R]( Cluster Analysis in R Dima Gorenshteyn, Senior Data Scientist at Memorial Sloan Kettering Cancer Center Cluster analysis is used to find groups of observations (clusters) that share similar characteristics. The course will cover two commonly used clustering methods - hierarchical clustering and k-means clustering. With these, you will explore three different datasets: soccer player positions, wholesale customer spending data, and longitudinal occupational wage data. [Start Learning]( Building Web Applications in R with Shiny: Case Studies: What You'll Learn Chapter 1: [Shiny review]( In the first chapter, you'll review the essentials of Shiny development. You'll get re-introduced to the basic structure of a Shiny application, as well as some core Shiny concepts such as inputs, outputs, and reactivity. Chapter 2: [Make the perfect plot using Shiny]( Imagine you're preparing a figure for a manuscript using R. To save you from the hassle of re-running the code many times, in this chapter you will learn how to create a Shiny app to make a customizable plot. Chapter 3: [Explore a dataset interactively with Shiny]( After being impressed by the plot you created with Shiny, your supervisor now wants an interactive environment where he can view the data, filter it, and download it. This chapter will guide you in creating this to explore the Gapminder dataset. Chapter 4: [Create your own word cloud in Shiny]( Your friend has written an R function for generating word clouds she wants to share with all her friends, but not all of them know how to use R. This chapter will guide you through creating an app to generate word clouds using a point-and-click interface. [Play Now]( Cluster Analysis in R: What You'll Learn Chapter 1: [Calculating distance between observations]( Cluster analysis seeks to find groups of observations that are similar to one another, but the identified groups are different from each other. In this chapter, you will learn how to calculate the distance between observations. Chapter 2: [Hierarchical clustering]( How do you find clusters in your data using the distances that you have calculated? You will learn about the fundamental principles of hierarchical clustering and will explore data from a wholesale distributor to perform market segmentation of clients. Chapter 3: [K-means clustering]( In this chapter, you will build an understanding of the principles behind the k-means algorithm, learn how to select the right k when it isn't previously known, and revisit the wholesale data from a different perspective. Chapter 4: [Case Study: National Occupational mean wage]( In this chapter, you will apply the skills you have learned to explore how the average salary amongst professions have changed over time. [Play Now]( [DataCamp] [DataCamp]( DataCamp Inc. | 350 Fifth Avenue | Suite 7730 | New York, NY 10118 [Facebook] [Facebook]( [Twitter] [Twitter]( [LinkedIn] [LinkedIn]( [YouTube] [YouTube]( [Unsubscribe](