Learning R through an Example
- 2 hours on-demand video
- 6 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- Learn the Basics of R Programming
- How to write R Program to create Word Cloud
- How to write R Program for generates Number in Words for a given Number
- Some Programming Skills
- Some knowledge of Statistics
This is an introductory program on R Programming. We go through the basics of R Language and take on some advanced topics like connecting to a Database and creating Presentations.
This course is targeted for people who are getting started with R programming. This course can be useful for student and professionals. This course is design especially for professionals in Executive positions who would like to process data for making managerial decisions.
- Beginners to Programming
- Executives who have stopped programming for quite a while
- Data Scientists
- Data Analysts
This is a primer in R Programming. However, we deal with some advanced concepts as well so that the program enables students and professionals to use R Language for their daily works.
In this chapter, we discuss the mechanism for reading data from files. We use a Comma Separated Values (CSV) File.
Then, we discuss some operations on the data that is read from the file. These operations are typical database operation what is needed for conduction on such data.
In this section, we will learn how to interface R with a Database. We will be using DB2 Database on IBM Cloud. However, the same concepts can be applied to connect to any other Database Engine.
Then, we will see how to create various types of Graphs. We will primarily use ggplot2 package of R.
Last, we will learn how to create Presentations using R.
In this chapter, we learn how to connect to a Database. We use DB2 database on IBM Cloud to illustrate the concepts. Using these concepts, we can connect to any Database Engine.
We then see how to fetch data from a Database. The command used for fetching data can also be used to update data in the Database.
Sentiment analysis (also known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.