ADVANCED EXPERT SYSTEMS
- Course
- MISY675 - ADVANCED EXPERT SYSTEMS
- Department
- Management Information Systems - English - PhD
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
Course Description
This course aims to explain expert systems which are artificial intelligent systems. The students will learn features and importance of expert systems. Students will learn, knowledge representation and the related programming languages. Students will learn how to develop rule based expert systems, blackboard expert systems, frame-based expert systems, fuzzy expert systems, and artificial neural networks expert systems. Also, they will learn the features and characteristics of hybrid intelligent systems. However, they will also learn the expert system architecture, inference mechanism, explanation module, and reasoning under uncertainty. Moreover, the students will learn the phases of developing an expert system, searching techniques used in AI. Also, areas of application of expert systems in management will be discussed
ADVANCED EXPERT SYSTEMS
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Course outcomes
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Course Syllabus
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Learning Outcomes
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Program Outcomes
- Demonstrate mastery of advanced research methodologies (quantitative, qualitative, and mixed methods) by critically analyzing literature, identifying research gaps, and designing original studies that contribute to MIS theory and practice.
- Conduct and defend an original doctoral dissertation that reflects independent scholarly inquiry, academic rigor, and a significant contribution to the advancement of knowledge in MIS.
- Exhibit readiness for thesis monitoring and defense by articulating the philosophical foundations of research paradigms, positioning one's research within these frameworks, and responding to scholarly critique.
- Apply ethical principles, academic integrity, and responsible conduct of research in all phases of the research process, including data collection, analysis, reporting, and publication.
- Identify and address the social, legal, and ethical implications of information systems research and its applications within organizational and societal contexts.
- Employ advanced data science techniques, including statistical modeling, machine learning, and AI-based analytics, to examine complex datasets and extract meaningful insights in MIS research.
- Recognize and evaluate emerging technologies such as artificial intelligence, big data, blockchain, and the Internet of Things, assessing their transformative impact on organizational processes and digital ecosystems.
- Collaborate and lead in interdisciplinary research environments, establishing productive scientific partnerships and managing research projects that integrate diverse academic perspectives.
- Publish high-quality research in peer-reviewed journals, present findings at international conferences, and actively engage in academic service such as journal reviewing, conference organizing, and committee participation.
- Identify challenges and propose innovative, research-based solutions at the intersection of information systems, technology, and organizational strategy.
- Deliver advanced-level MIS courses, supervise graduate research, and nurture academic development through effective mentorship and scholarly teaching.
- Develop advanced information systems and decision support systems that align IT capabilities with organizational strategies using systems thinking and innovative design methodologies.
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