1. SylabUZ
2. Wydział Informatyki, Elektrotechniki i Automatyki
3. semestr zimowy 2020/2021
4. Informatyka - Program Erasmus drugiego stopnia
5. Social networks and multi-agent systems

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Social networks and multi-agent systems - opis przedmiotu

Cel przedmiotu

To familiarize students with the genesis, architecture and properties of social networks. Big Data and the role that social networks play in the context of large-scale data generation. Developing basic skills in the analysis of media and social networks using Big Data technology. Introduction to multi-agent systems used for modeling social networks.

 

Wymagania wstępne

Zapisz zmiany

Databases, Basic knowledge of statistics, Ability to program in Java, Knowledge of Big Data technology

Zakres tematyczny

Multi-agent systems as modern tools for distributed intelligence systems engineering. The use of multi-agent systems to build autonomous control mechanisms in the context of cloud computing. Definition of media and social networks. Types of social networks and characteristics of their functioning. Social media and Big Data as new trends setting the direction of IT development. Acquiring data from social media and their analysis using Big Data technology. Application of machine learning algorithms for advanced analysis of data obtained from social media.

Metody kształcenia

lecture: Conventional lecture, discussion, problem lecture,

laboratory exercises: teamwork, group work,

project: project method, group work, brainstorming

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Students are assessed on the basis of:

Own project (50% of the grade) - the project verifies the achievement of learning outcomes in terms of practical skills. The project should include the implementation of the selected design task with documentation.

An exam (50% of the grade) of a written or oral nature. Students are admitted to the exam on condition that they receive credit for laboratory exercises during which their practical ability to perform tasks useful during the implementation of group projects will be assessed.

 

Literatura podstawowa

Michael Wooldridge, An Introduction to MultiAgent Systems - Second Edition, 2009
Duncan J. Watts, Six degrees: the science of a connected age, 2003
Morzy T.: Eksploracja danych. Metody i algorytmy, PWN, Warszawa, 2013
Markov Z., Larose D.T.: Eksploracja zasobów internetowych, PWN, Warszawa, 2009
White T., Hadoop: The Definitive Guide, 3rd Edition, O'Reilly Media / Yahoo Press, 2012
George L., HBase: The Definitive Guide, O'Reilly Media, 2011

Literatura uzupełniająca

Stanton J.M.: Introduction to Data Science, E-book, 2013

 

Uwagi

Opracował: dr inż. Mariusz Jacyno, dr inż. Jacek Bieganowski

Zmodyfikowane przez dr inż. Jacek Bieganowski (ostatnia modyfikacja: 26-04-2020 12:26)