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title: Learning Outcomes
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*The Learning Outcomes are taken from the
[Module Description](https://www.ntnu.edu/studies/courses/IE502014#tab=omEmnet).
Only the layout has been changed, for the sake of legibility.*
# Knowledge
Upon completion of the course, students should be able to
- describe AI in terms of the analysis and design of intelligent agents or systems that interact with their environments
-explain relevant AI terminology, models, and algorithms used for problem solving
- explain relevant AI terminology, models, and algorithms used for problem solving
# Skills
Upon completion of the course, students should be able to
- model problems in suitable state space depending on choice of solution method
- simulate models and solve problems by means of AI methods, e.g., search algorithms or computational intelligence
- analyse models, AI methods, and simulation results
# General competence
Upon completion of the course, students should be able to
- read and understand scientific publications and textbooks on AI and reformulate the presented problems, choice of methods, and results in a short, concise manner
- discuss and communicate advantages and limitations of selected AI methods for problem solving