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Computational Intelligence and Decision Making– P170M109

Computing
Open for application
6 ECTS

MODULE TYPE: SDG11 

MODULE DESCRIPTION

This course provides a comprehensive introduction to computational intelligence through the machine learning and intelligent decision making systems. The course covers the basics: Linear Discriminants analysis, Support Vector Machines, Learning with Trees, Ensemble Learning, Probabilistic Modelling, Unsupervised and Semi-Supervised Learning, Online learning strategies, Optimization and Search, Evolutionary learning, Markov chain Monte Carlo method and others. The course will also draw from numerous case studies and applications, so that you'll also learn how to use and integrate machine learning methods into the decision making system. Practical tasks are provided in MATLAB environment.

LEARNING OUTCOMES

Get knowledge about the most popular machine learning methods, know possibilities of applications and understand the principles of learning algorithms.

Get knowledge about decision making systems, basic components and principles of creating architecture.

Ability to implement machine learning methods in MATLAB environment. Make comparative result analysis of selected methods.

Ability to select and apply the most suitable machine learning method(s) depending on the given problem.

Ability to integrate machine learning methods into the decision making systems.

Module level: Advanced

Degree level: Master

Language: English

Study mode: Online

SDG11 Theme: Resilient communities

ECTS: 6

Semester: Autumn

Starting date: 1 September 2021

Finishing date:  15 January 2022 

Enrollment period: 15 August 2021

Additional Info: Max 30 students

Participation form: Please fill this document and send it to the admission-contact person: eciu-university@ktu.lt 

University

Kaunas University of Technology

Participation info

The admission is currently possible for learners from ECIU partner universities. Please fill the above form and send it to the admission-contact person: eciu-university@ktu.lt