Introduction to R and Data Mining
The module aims to introduce students to the programming language for statistical computing, R. As a practical learning experience, it introduces fundamental skills for working with data by using data mining essentials as an application context. It provides an overview of R and applies it to the key stages of the data mining process: importing, inspecting, cleaning, and exploring data, as well as finding and visualizing patterns. Organized as a case study, the module focuses on asking and answering questions in R rather than a theory-oriented introduction, in order to provide practical skills and an understanding of data driven pattern discovery.
Dimitar Slavov
Dimitar Slavov
A first-year MSc in Software and Data Engineering student at USI, passionate about working with data and deploying innovative technologies across a range of sectors, with a strong interest in interdisciplinary areas, from databases and working with data in various formats to applying statistical learning methods for a variety of applications.
Data mining with R is a key area of interest for me. Over the years, my experience applying diverse data mining techniques to large datasets has strengthened my understanding of different data types and dataset sizes, as well as how to efficiently use R to extract meaningful insights.