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Social networks and multi-agent systems - course description

General information
Course name Social networks and multi-agent systems
Course ID 11.3-WE-INFD-SNaM-AS-Er
Faculty Faculty of Engineering and Technical Sciences
Field of study WIEiA - oferta ERASMUS / Informatics
Education profile -
Level of studies Second-cycle Erasmus programme
Beginning semester winter term 2018/2019
Course information
Semester 2
ECTS credits to win 6
Course type obligatory
Teaching language english
Author of syllabus
  • dr inż. Jacek Bieganowski
Classes forms
The class form Hours per semester (full-time) Hours per week (full-time) Hours per semester (part-time) Hours per week (part-time) Form of assignment
Lecture 30 2 - - Exam
Laboratory 15 1 - - Credit with grade
Project 15 1 - - Credit with grade

Aim of the course

To introduce students to modern software engineering approaches that utilize agent-based technology. To outline new Internet technologies, including social media and to explain how social networks can be employed for Big Data analytics. To characterize modern techniques and solutions for performing analytics on large sub sets of data.

Prerequisites

Java programming.

Scope

Intelligent agents and multi-agent systems. Architecture and design of intelligent agents. Coordination mechanisms for multi-agent systems. Engineering of autonomic and complex software systems using agent-based technology. Social networks. Properties of social networks. The role and application of social networking in e-business. Mechanisms for managing and monitoring social systems. Big Data and social media analysis. Phenomenon of Big Data. Application of Big Data within the context of e-business. Tools and technologies for performing analytics on large scale.

Teaching methods

Lecture, laboratory exercises, project.

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

Lecture – the passing condition is to obtain positive mark from the exam.

Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned within the laboratory schedule.

Project – the passing condition is to obtain positive mark from the project.

Recommended reading

1. Wooldridge M.: Multi-agent systems (second edition), MIT Press, 2013

2. Watts J. D.: Six degress: the science of a connected age, W.W. Norton & Company, 2003

3. White T.: Hadoop: The Definite Guide (third edition), O'Reilly Media, 2012

4. Owen S., Anil R., Dunning T., Fridman E.: Mahout in action, Manning Publications, 2011

Further reading

Notes


Modified by dr inż. Jacek Bieganowski (last modification: 23-04-2018 09:10)