| Code | DE0743 | ||||||||||||||||||||||||||||||||||||||||||||
| 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 | ||||||||||||||||||||||||||||||||||||||||||||
| Credit points | 6.0 | ||||||||||||||||||||||||||||||||||||||||||||
| 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.. |
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| Contents |
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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. | ||||||||||||||||||||||||||||||||||||||||||||
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Learning outcomes and assessment |
Knows the types of intelligent agents, their characteristics, is capable to choose suitable agents and apply them to solve problems of various domains. - Laboratory work about objects and agents. Corresponding problems in the examination and midterms. Practical classroom works. Knows the classic artificial intelligence methods, is capable choose suitable methods and apply them to solve problems of various domains. - Laboratory works about search and planning agents. Corresponding problems in the examination and midterms. Practical classroom works. Knows and is able to apply the machine learning methods, is capable to use them to address various business domain problems. - Laboratory work about decision trees and neural networks. Corresponding problems in the examination and midterms. Practical classroom works. |
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| Evaluation criteria of study results |
Exam - 40%
Homework - 40% Midterms and classroom work - 20% |
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| Course prerequisites | None | ||||||||||||||||||||||||||||||||||||||||||||
| Course planning |
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