Dettagli sull'Insegnamento per l'A.A. 2018/2019
Nome:
Big Data: Models And Algorithms / Big Data: Models And Algorithms
Informazioni
Crediti:
: Master Degree in Computer Science 3 CFU (d)
Erogazione:
Master Degree in Computer Science 2nd anno curriculum NEDAS Elective
Lingua:
Inglese
![[info]](img/info16.png)
Prerequisiti
Basic courses in algorithms and data structures. Mathematical and programming maturity.
Basics of data analysis.
Obiettivi
To know and be able to design, analyze and implement algorithms for massive data sets using
state-of-the-art algorithmic techniques in the area. To know and be able to apply experimental
algorithmic techniques. To know alternative processing models that are relevant to big data.
Sillabo
- Data Mining
- Algorithmic techniques and models for massive data sets
- Experimental algorithmics
Descrittori di Dublino
Alla fine del corso, lo studente dovrebbe
- Be able to describe in a comprehensible manner, analyze, evaluate, and compare the
performance of algorithms, with a focus on models of computation relevant to massive
data sets.
- Be able to systematically identify and analyze problems and make informed choices for
solving the problems based on the analysis
- Be able to design and implement algorithms for problems related to massive data sets
through state-of-the-art software frameworks
- Be able to lookup and apply relevant research literature for problems related to massive
data sets
- Be able to Express oneself in writing at a scientific level
- Know the foundations of the algorithmic experimental process design
Testi di riferimento
- Catherine McGeoch, A Guide to Experimental Algorithmics
- J. Leskovec, A. Rajaraman, J. D. Ullman, Mining of Massive Datasets. 2nd Edition
- Sean Luke, Essentials of Metaheuristics, 2nd Edition
Modalità d'esame
Written Exam + Oral discussion (and/or Homework/Project)
Aggiornamenti alla pagina del corso
Le informazioni sulle editioni passate di questo corso sono disponibili per i seguenti anni accademici:
Per leggere le informazioni correnti sul corso, se ancora erogato, consulta il catalogo corsi di ateneo.
Ultimo aggiornamento delle informazioni sul corso: 01 marzo 2018, 11:01
English version
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