Data Science is an interdisciplinary field whose main aim is the development of methods, processes and systems for extracting knowledge from unstructured or structured information. It concerns a new approach to addressing the ever-increasing need for data analysis, which has emerged in recent years with the explosion of the internet and the emergence of huge volumes of data in many applications.
The goal of this course is to present and critically understand advanced algorithmic techniques for analyzing large volumes and complexity of data. The following topics are covered: models and programming techniques for processing large amounts of data; complexity of algorithms for big data; association rules through frequent itemsets; locality-sensitive hashing; clustering; dimensionality reduction; link analysis of huge graphs (e.g., PageRank); social network analysis and community detection; recommendation systems; algorithms for large data streams. Particular emphasis is given to fundamental algorithmic techniques for analyzing and processing large amounts of data, as well as their applicability to a variety of practical applications.