Course Unit


Big data models and algorithms

Unit Coordinator: Mattia D'Emidio
Programme: Erasmus Mundus, Double Degrees
ECTS Credits: 3
Semester: 2
Year: 1
Campus: University of L'Aquila
Language: English

Upon completion of this course the student will have reliably demonstrated the ability to design, analyze and implement algorithms for massive data sets using state-of-the-art algorithmic techniques in the area.

Furthermore, the student will be able to understand:

i) storage strategies that are suited for large-scale datasets (e.g. distributed, unstructured);

ii) alternative processing models that are relevant to big data;

iii) fundamentals of large-scale data mining.

Finally, the student will acquire basic knowledge of experimental algorithmic techniques and data analysis.


Large-Scale Data Mining Models, Algorithms, Storage Techniques for Massive Datasets


Basic courses on design and analysis of algorithms and data structures. Mathematical and programming maturity. Fundamentals of data analysis.

Reading list:

J. Leskovec, A. Rajaraman, J. D. Ullman. Mining of Massive Datasets. 2nd Edition.


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InterMaths Network
A network of 12 European Universities, coordinated by Department of Information Engineering, Computer Science and Mathematics (DISIM) at University of L'Aquila in Italy (UAQ)