DSP705 Artificial Intelligence in Business

Code DSP705
Name Artificial Intelligence in Business
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Academic
Field of study Computer Science
Faculty
Academic staff Ilze Andersone, Egons Lavendelis
Credit points 4.0 (6.0 ECTS)
Parts 1
Annotation Artificial intelligence includes rather new technologies that can be used to solve complex business problems in different domains. The information technology specialist must be able to select the most suitable artificial intelligence technologies for business problems. The main topic is their usage for practical business problem solving. Different programming approaches are reviewed to show origins of the agent oriented programming and differences from other approaches. Overview of various types of agents and their applications is given in the course. Intelligent mechanisms, like planning, knowledge representation, inference and machine learning are covered, too. Already developed agent projects are analysed illustrating what types of agents are suitable for what projects. Algorithms used in artificial intelligence and their implementations as well as the agent oriented software engineering process are covered in the practical part of the course..
Goals and objectives
of the course in terms
of competences and skills
The goal of the course is to give understanding of the advanced artificial intelligence technologies and abilities to apply these technologies to solve various complex business problems. The main objectives of the course are the following: To acquire different programming approaches, especially the agent oriented programming. To study intelligent agents and multi-agent systems, their development and applications, as well as to be able to apply agents and multi-agent systems to solve various business problems. To study various artificial intelligence solutions and know their applicability.
Learning outcomes
and assessment
Knows different programming approaches and possibilities to apply them. - Practical work about objects and agents. Corresponding problems in the examination.
Knows and is able to apply the latest solutions of artificial intelligence. - Laboratory work about decision trees and neural networks. Independent research about already developed agent projects. Corresponding problems in the examination.
Knows the types of intelligent agents, their characteristics, is capable to choose suitable agents and apply them to solve problems of various domains. - Independent research about already developed agent projects.
Knows agent interaction mechanisms and is capable to design the mechanisms for different applications. - Practical work about agent interaction mechanisms. Corresponding problems in the examination.
Understands intelligent mechanisms used in agents and is capable to choose the most suitable one(-s) for a specific system. - Laboratory works about intelligent mechanisms used in agents. Corresponding problems in the examination.
Has a good knowledge about agent oriented software engineering process and is capable to carry out activities corresponding to the analysis and design phases. - Practical works about analysis and design phases of the agent oriented software engineering process. Corresponding problems in the examination.
Course prerequisites None

[Extended course information PDF]