Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty of Engineering
  • Department of Computer Engineering (English)
  • Course Structure Diagram with Credits
  • Artificial Intelligence
  • Learning Outcomes
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

  • Will be able to explain the fundamental concepts of Artificial Intelligence.
  • Gains a historical perspective on Artificial Intelligence and its foundations.
  • Describes the major applications, topics, and research areas of Artificial Intelligence.
  • Characterizes the goals of Artificial Intelligence, approaches to those goals, and progress toward those goals.
  • Will be able to comprehend the underlying principles of the Artificial Intelligence approach to problem-solving.
  • Explains the concept of an intelligent agent.
  • Describes the basic components of an intelligent agent.
  • Compares different types of intelligent agents.
  • Will be able to apply search-based problem-solving techniques.
  • Comprehends the role of search in Artificial Intelligence.
  • Explains the basic types of search algorithms.
  • Discusses the computational complexities of search algorithms.
  • Differentiates between uninformed and heuristic (informed) state-space search algorithms.
  • Will be able to develop adversarial (game) algorithms.
  • Describes the role of games in the history of Artificial Intelligence.
  • Implements algorithms for playing simple games.
  • Will be able to explain the core concepts and algorithms of Constraint Satisfaction Problems
  • Applies constraint satisfaction to techniques in solving problems.
  • Describes several heuristics used in constraint satisfaction problems.
  • Will be able to define machine learning, basic concepts, and methods used in machine learning.
  • Explains the basic concepts in machine learning.
  • Lists various applications of machine learning.
  • Gains a basic understanding of different machine learning approaches.
  • Differentiates between various machine learning algorithms by identifying, assessing, and reasoning about their advantages and disadvantages.
  • Selects the most suitable machine learning algorithm for a given application or task.
  • Will be able to describe concepts, methods, and theories of logic and probability theory, and analyze the power and limitation of their use for knowledge representation and reasoning systems.
  • Applies logic rules to write statements, operate on statements, and to transform a statement into equivalent statements.
  • Makes inferences and proves statements in logic.

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