In this course, learn how to encode data for a data set based on customer retail purchases. From cleaning and preparing data, to finding simple and powerful frequency analysis, you will make an impact quickly in businesses and organizations. Throughout the course you will use R, one of the best and most popular statistical computing languages. Some experience with R and RStudio will help.
Encoding Data can be time consuming and lacks proper data insights in the process. In this course, Encoding Data with R, you will gain the ability to encode data to utilize a data set, while being able to find data frequencies and insights that fit your data set and business goals. First, you will learn the factor() function for converting data types. Next, you will discover how to find data frequencies through the table() function. Finally, you will explore how to encode data for a indicator flag or for a potential model. When you are finished with this course, you will have the skills and knowledge to encode data to find insights quickly.
Emilee has an M.S. in Business Statistics from Mercer University and currently works as a Data Scientist. She has worked with data for 5+ years, spending the majority of her time in financial industry. She created marketing solutions at an investment management firm, consulted with lenders on risk models at a credit bureau, and currently works in consumer banking. Through her love of data, she has always had a passion for teaching. Prior to grad school, she worked as a teacher.
Course Overview Hi, everyone. My name is Emilee McWilliams, and welcome to the course, Encoding Data with R. I'm a data scientist in the financial industry, and I've seen a variety of business problems solved through data analysis. At many times in data projects, factor, or categorical‑level data, needs cleaning and processing in order to be utilized in analysis. In this course, we will be encoding data based on a data set of customer purchases, and we'll understand the analysis. Some of the major topics we'll cover include understanding factor‑level data, creating frequency analysis from this data, encoding factor‑level data for a database, and preparing data for a potential model. By the end of this course, you'll know how to encode factor‑level data, prepare it, and find data insights from the analysis. Before beginning this course, you should be familiar with the basics of R and RStudio. I hope you'll join me on this journey to learn R with the Encoding Data with R course, at Pluralsight.