Disclaimer: If you sign up for a (paid) course using this link, R-exercises earns a commission. It does not impact what you pay for a course, and helps us to keep R-exercises free.Course Description
Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before
Data mining is a growing demand on the market as the world is generating data at an increasing pace. R is a popular programming language for statistics. It is very useful for day-to-day data analysis tasks.
Data mining is a very broad topic and takes some time to learn. This Learning Path will help you to understand the mathematical basics quickly, and then you can directly apply what you’ve learned in R. This Learning Path explores data mining techniques, showing you how to apply different mining concepts to various statistical and data applications in a wide range of fields.
This Learning Path is the complete learning process for data-happy people. We begin with a thorough introduction to data mining and how R makes it easy with its many packages. We then move on to exploring data mining techniques, showing you how to apply different mining concepts to various statistical and data applications in a wide range of fields using R’s vast set of algorithms.
The goal of this Learning Path is to help you understand the basics of data mining with R and then get you working on real-world datasets and projects.
This Learning Path is authored by some of the best in their fields.
What are the requirements?
- Requires basic knowledge of R
What am I going to get from this course?
- Get to know the basic concepts of R: the data frame and data manipulation
- Explore graphs and the statistical measure in graphs
- Implement various dimension reduction techniques to handle large datasets
- Acquire knowledge about the neural network concept drawn from computer science and its applications in data mining
- Work with complex data sets and understand how to process data sets
- Apply data management steps to handle large datasets
- Create predictive models in order to build a recommendation engine
Who is the target audience?
- This course is ideal for data analysts from novice to intermediate level. You should have prior knowledge of basic statistics and some programming language experience in any tool or platform. Familiarity with R will be an added advantage.