FACULTY OF ARTS AND SCIENCES
Department of Mathematics
SOCIAL MEDIA
SE 420 | Course Introduction and Application Information
| Course Name |
Artificial Intelligence and Expert Systems
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
SE 420
|
Fall/Spring
|
3
|
0
|
3
|
5
|
| Prerequisites |
None
|
|||||
| Course Language |
English
|
|||||
| Course Type |
Elective
|
|||||
| Course Level |
First Cycle
|
|||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | - | |||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | The goal of this course is to provide students with a survey of different aspects of Artificial Intelligence (AI). |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | This course provides an introduction to Artificial Intelligence (AI). In this course we will study a number of theories, mathematical formalisms, and algorithms, that capture some of the core elements of computational intelligence. We will cover some of the following topics: search, logical representations and reasoning, automated planning, representing and reasoning with uncertainty, decision making under uncertainty, and learning. |
|
|
Core Courses | |
| Major Area Courses | ||
| Supportive Courses |
X
|
|
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Introduction to AI Introduction to Expert Systems | |
| 2 | Introduction to AI, Intelligent Agents, Examples to AI Languages | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 3 | Problem Solving by Search I | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 4 | Problem Solving by Search II | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 5 | Problem Solving by Search III | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 6 | Expert Systems I | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 7 | Midterm | |
| 8 | Expert Systems II | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 9 | AI: Language Processing | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 10 | AI: Machine Learning I | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 11 | AI: Machine Learning II | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 12 | AI: Information Retrieval | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 13 | Presentations | |
| 14 | Presentations- Review of the Semester | |
| 15 | Review of the Semester | |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114.
Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| Suggested Readings/Materials | Internet |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques |
4
|
20
|
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | ||
| Project |
1
|
20
|
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
20
|
| Final Exam |
1
|
40
|
| Total |
| Weighting of Semester Activities on the Final Grade |
6
|
60
|
| Weighting of End-of-Semester Activities on the Final Grade |
1
|
40
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
| Study Hours Out of Class |
15
|
2
|
30
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
4
|
3
|
12
|
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
1
|
0
|
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
20
|
20
|
| Final Exam |
1
|
40
|
40
|
| Total |
150
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
||
| 1 | To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics. |
|||||
| 2 | To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics. |
X | ||||
| 3 | To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials. |
|||||
| 4 | To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning. |
X | ||||
| 5 | To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals. |
X | ||||
| 6 | To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project. |
X | ||||
| 7 | To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge. |
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| 8 | To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field. |
|||||
| 9 | To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security. |
X | ||||
| 10 | To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking. |
|||||
| 11 | To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language. |
|||||
| 12 | To be able to speak a second foreign language at a medium level of fluency efficiently. |
X | ||||
| 13 | To be able to relate the knowledge accumulated throughout the human history to their field of expertise. |
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*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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