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| Course: | INFO370 - Artificial Intelligence Information Systems |
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| On Campus Offering: | Winter (eve) |
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| Online Offering: | Spring |
| | Faculty: | Weber, Rosina
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| Extended Course Description: | Catalog Course Description:
Introduction to the field of artificial intelligence (AI). Basic concepts, principles, and techniques used to achieve the goals of AI are studied. Examples and applications are specific to information systems.
Pre-requisites and Co-requisites:
PHIL 111 Beginning Logic
CS 390 Data Structures OR CS 260 Data Structures
Curriculum Role:
This is an elective course.
Course Rationale:
This course is usually taken by juniors and seniors who have already taken the systems analysis courses. After they learned the principles of information systems, in this course they learn how information systems can be enhanced to perform complex tasks with artificial intelligence methods. This course is complemented by courses in natural Language and expert systems. It is broad in that it introduces and covers several AI methods but it also allows students to learn one or two methods in depth.
Course Outcomes:
Upon successful completion of this course, the students will be able to:
• Recognize major approaches in Artificial Intelligence (e.g., state spaces and search, heuristic techniques, knowledge representation, connectionist models);
• Judge and Justify why some methods can be used for some problems
• Distinguish knowledge-bases from databases
• Distinguish knowledge from data and information
• Recognize the major knowledge representation methods
Course Content:
Principal topics and the approximate number of weeks devoted to each are:
• Scope of the field of AI (0.33)
• Knowledge representation (1.67)
• Problem solving methods (0.33)
• Heuristic search (2)
• Rule-based systems (1)
• Constraint-based reasoning (1)
• Logic and theorem proving (2)
• Special topics of interest to students (1)
Presentation:
Note: Presentation method may vary somewhat from section to section.
The mode of presentation is by lecture and class discussion.
Assessment:
Note: Assessment method may vary somewhat from section to section.
Evaluation is by examination and homework assignments.
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