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Cyprus International University
TR

ARTIFICIAL INTELLIGENCE

Course
CPE415 - ARTIFICIAL INTELLIGENCE
Department
Management Information Systems - English - Undergraduate
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
0
T+P+L
3 + 0 + 0
Course Coordinator(s)
Assoc. Prof. Dr. Kamil YURTKAN
Prerequisite
-
Keywords
-

Course Description

-

ARTIFICIAL INTELLIGENCE

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

  1. 01 gain an understanding of the key components of the artificial intelligence (AI)
  2. 02 gain an understanding of the agent-based AI architecture
  3. 03 apply artificial intelligence techniques and classifiers in solving problems of a particular domain
  4. 04 implement basic learning algorithms in machine learning
  5. 05 represent knowledge using various techniques

Course Syllabus

Week Topic
Week 1 Introduction to AI and Problem Solving
Week 2 Intelligent Agents
Week 3 Intelligent Agents
Week 4 Introduction to Machine Learning
Week 5 Introduction to Neural Networks - Perceptron Learning
Week 6 Introduction to Neural Networks - Feed Forward Neural Networks
Week 7 Introduction to Neural Networks - Hopfield Network
Week 8 Uninformed Search Strategies - Breadth First Search, Uniform Cost Search, Depth First Search
Week 9 Uninformed Search Strategies - Breadth First Search, Uniform Cost Search, Depth First Search
Week 10 Midterm Week
Week 11 Midterm Week
Week 12 Informed Search Strategies - Greedy Search , A* Search
Week 13 Informed Search Strategies - Greedy Search , A* Search
Week 14 Representation and Logic - Propositional Logic
Week 15 Representation and Logic - First Order Logic

Reference Books & Course Materials

  1. 01 S. Russell, P. Norvig, "Artificial Intelligence: A Modern Approach", Prentice-Hall, 2003.
  2. 02 Simon Haykin, Neural Networks: A Comprehensive Foundation 2nd Ed. Prentice Hall PTR Upper Saddle River, NJ, USA ©1998 ISBN:0132733501

Learning Outcomes

No learning outcomes have been defined.

Program Outcomes

  1. P01 Be able to apply knowledge of programming
  2. P02 Be able to design software systems of varying complexity
  3. P03 Be able to identify, categorize, and develop solutions for computer orientated challenges.
  4. P04 Be able to demonstrate autonomy and responsibility in managing computer programming projects
  5. P05 Be able to follow the state of the arts concepts in computer technology
  6. P06 Be able to design, implement, and evaluate a computational system to meet desired needs within realistic constraints.
  7. P07 Be able to use appropriate techniques, skills, and tools necessary for computing practice.
  8. P08 Be able to apply appropriate technologies and techniques for the collection and analysis of organizational and environmental data to facilitate evidence-based decision making
  9. P09 Be able to apply effective communication skills consistent with the professional environment -
  10. P10 Be able to apply effective collaboration skills in teamwork consistent with the professional environment -

Po-Lo Matrix

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