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Hands-On Data Analytics with R

Video Description

Explore a variety of statistical and Machine Learning techniques using R

About This Video

  • Accelerate your data analytic capabilities from a basic understanding to being able to apply and interpret results effectively, providing deep insight into a plethora of data-driven scenarios
  • Contains the maximum amount of practical examples and mini-tests with minimal lecturing to encourage a natural and self-rewarding progression
  • Perform and interpret results from the most commonly used statistical and ML techniques used by data professionals such as linear models, k-means clustering, and Principal Component Analysis.

In Detail

This course will expand your understanding of statistics so you can* create analytic models in R. High-level data science techniques will be presented to you in a practical manner, to help you bridge the gap between the questions you wish to answer, the data used for analysis, and how to create some of the classic models used in data analytics.

You will start off by understanding dimensionality reduction and data mining in R and learning how to simplify complex datasets and unearth patterns from data. Moving on, you will understand hypothesis testing and p-values. You will also demonstrate one-sample and two-sample tests and the benefits they provide as very sophisticated analytical techniques. You will understand how data can give you predictive insights into the future and will conclude by presenting data in a way that will allow you to answer questions with data-driven confidence.

By the end of the course, you will be capable of utilizing R's statistical prowess to analyze a variety of datasets and present these insights effectively.

All the code files for this course are available on Github at - https://github.com/PacktPublishing/Hands-On-Data-Analytics-with-R--V-

Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.