CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Artificial Intelligence BİL481 FALL-SPRING 2+0 E 4
    Learning Outcomes
    1-define a well-defined problem formulation for a complex problem
    2-design intelligent agents
    3-solve well-defined problems using artificial intelligence methods and algorithms
    4-design problem solving agents
    5-develop inference mechanisms and planning capabilities for agents
    6-add learning capabilities to agents
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14456
    Assignments0000
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)30166
    Project30188
    Laboratory 0000
    Final exam (exam + preparation) 4011010
    0000
    Total Workload (hours)   122
    Total Workload (hours) / 30 (s)     4,07 ---- (4)
    ECTS Credit   4
  • Course Content
  • Week Topics Study Metarials
    1 Introduction to Artificial Intelligence R1-Chapter-1
    2 Intelligent Agents R1-Chapter-2
    3 Well-Defined Artificial Intelligence Problems R1-Chapter-4
    4 Problem Solving and Search-I R1-Chapter-3
    5 Problem Solving and Search-II R1-Chapter-3
    6 Constraint Satisfaction Problems-I R1-Chapter-6
    7 Constraint Satisfaction Problems-II R1-Chapter-6
    8 Review of Problem Solving R1-Chapter-6, R2-Chapter-3
    9 Game Playing R1-Chapter-5
    10 Proposotional Logic R1-Chapter-8
    11 Inference in Proposotional Logic R1-Chapter-9
    12 Planning and Learning in Agents R1-Chapter-10
    13 Machine Learning and Deep Learning-I R2-Chapter-4,5
    14 Machine Learning and Deep Learning-I R2-Chapter-4,5
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assist. Prof. Dr. Seda Şahin
    Instructors -
    Assistants -
    Resources R1. Artificial Intelligence: A Modern Approach (3rd Edition), Stuart Russell, Peter Norvig, Prentice Hall, 2010. R2.J. O DONNELL, Discrete Mathematics Using a Computer, Springer, 2006, ISBN 978-1-84628-2.
    Supplementary Book -
    Goals To teach the concepts of Artificial Intelligence.
    Content Intelligent Agents, Well-Defined Artificial Intelligence Problems, Problem Solving and Search, Constraint Satisfaction Problems, Review of Problem Solving, Game Playing, Proposotional Logic, Inference in Proposotional Logic, Planning and Learning in Agents, Machine Learning and Deep Learning
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To be able to apply mathematics, science and engineering theories and principles to Computer Engineering problems. 5
    2 To have the ability to define, model, and solve problems related to Computer Engineering. 5
    3 To be able to design and conduct experiments, as well as to analyze and interpret data. 4
    4 To be able to design and analyze a process for a specific purpose within technical and economical limitations. -
    5 To be able to use modern techniques and calculation tools required for engineering applications. 4
    6 To have the awareness of professional liabilities and ethics. -
    7 To be able to get involved in interdisciplined and multidisciplined team work. -
    8 To be able to declare his/her opinions orally or written in a clear, concise and brief manner. -
    9 To improve him/herself by following the developments in science, technology, modern issues, and know the importance of lifelong learning. -
    10 To be able to evaluate engineering solutions for the global and social problems especially for the health, safety, and environmental problems. -
    11 To have knowledge about of contemporary issues. 4
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