<p>Data is everywhere and growing faster than ever before. It has now become challenge to deal with such huge amount of data as it is highly time-consuming. This has created a huge demand for people who can mine and interpret data. There is enormous value in data processing and analysis—and that is where a data scientist steps into the spotlight.</p> <p>This course will help candidates having basic knowledge of R Programming elevate to the next level. R can be used to tease actionable insights out of gigabytes of data, and this course will show you exactly how to do it. Here, we will be building on the advanced and efficient ways of doing different parts of analytics- right from data cleaning, visualizing to building high performing models You’ll start your journey by loading data, visualizing it and interpreting it while providing intuitive solutions. Further, you will learn to apply machine learning algorithms to real-world problems in R.</p> <p>By the end of the course, get geared up to tackle real-life data challenges by analyzing complex datasets. This in turn will bring out insights that companies can convert into actions.</p> <p>You can find the codes of this course on GitHub:&nbsp;<a href="https://github.com/PacktPublishing/Programming-for-Data-Science-with-R-" target="_blank">https://github.com/PacktPublishing/Programming-for-Data-Science-with-R-</a></p> <h1>Style and Approach</h1> <p>The course follows a practical approach while representing each technique to be applied on data-sets. Each section focuses on building of concept followed by hands-on-programming exercises. Throughout the course we’ll be discussing practical real-life cases for each concept. Our case study approach is designed to enable candidates to develop thorough understanding of concepts and will help them apply using R.</p>