ECTS - Introduction to Artificial Intelligence
Introduction to Artificial Intelligence (CMPE462) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
---|---|---|---|---|---|---|---|
Introduction to Artificial Intelligence | CMPE462 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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(CMPE323 veya SE328) |
Course Language | English |
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Course Type | Technical Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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Course Objectives | The objective of this course is to introduce basic concepts in both symbolic and non-symbolic approaches to Artificial Intelligence (AI). |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Agent Paradigm, Problem Solving by Searching, Informed/Uninformed Search Methods, Genetic Algorithms, Simulated Annealing, Constraint Satisfaction Problems, Adversarial Search, Ant Colony Optimization, Particle Swarm Optimization, Artificial Bee Colony Optimization, Multi-Agent Systems & Intelligent Agents, Multi-Agent Interactions, Philosophical Foundations & Ethics. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Agent Paradigm | Chapters 1-2 (main text) |
2 | Agent Paradigm | Chapter 1-2 |
3 | Problem Solving by Searching, | Ch 3 |
4 | Informed/Uninformed Search Methods | Ch. 4 |
5 | Genetic Algorithms and Simulated Annealing | Ch. 4 |
6 | Constraint satisfaction problems | Ch. 5 |
7 | Adversarial Search | Ch. 6 |
8 | Logical Agents | Ch. 7 |
9 | Knowledge Engineering | Resource #5 |
10 | Expert Systems | Resource #4 |
11 | Expert Systems | Resource #4 |
12 | Communication | Ch. 22 |
13 | Communication | Ch. 22 |
14 | AI Applications | Resource #3 |
Sources
Course Book | 1. Artificial Intelligence: A Modern Approach (Second Edition). Stuart Russell and Peter Norvig Prentice-Hall, 2003, ISBN: 0-13-790395 |
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Other Sources | 2. 1. Artificial Intelligence, Patrick H. Winston, Addison-Wesley, 1992. ISBN: 0-201-533774. |
3. 2. http://www.cs.rmit.edu.au/AI-Search/Product/ | |
4. 3. “Engineering Applications of Artificial Intelligence” journal, ISSN: 0952-1976, Elsevier, B.V. | |
5. 4. Expert Systems: Principles and Programming, Fourth Edition by Joseph C. Giarratano and Gary D. Riley, PWS Publishing Company, 2004. | |
6. 5. Knowledge Representation and Reasoning, Ronald Brachman and Hector Levesque, The Morgan Kaufmann Series in Artificial Intelligence , 2004. |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 3 | 35 |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 25 |
Final Exam/Final Jury | 1 | 40 |
Toplam | 5 | 100 |
Percentage of Semester Work | 60 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | X |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Adequate knowledge in mathematics, science and subjects specific to the computer engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. | X | ||||
2 | The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
3 | The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. | X | ||||
4 | The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in computer engineering applications; the ability to utilize information technologies effectively. | |||||
5 | The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the computer engineering discipline. | X | ||||
6 | The ability to work effectively in inter/inner disciplinary teams; ability to work individually | |||||
7 | Effective oral and writen communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions. | X | ||||
8 | The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions. | |||||
9 | Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology. | X | ||||
10 | The ability to behave according to ethical principles, awareness of professional and ethical responsibility; | X | ||||
11 | Knowledge of the standards utilized in software engineering applications | |||||
12 | Knowledge on business practices such as project management, risk management and change management; | |||||
13 | Awareness about entrepreneurship, innovation | |||||
14 | Knowledge on sustainable development | |||||
15 | Knowledge on the effects of computer engineering applications on the universal and social dimensions of health, environment and safety; | |||||
16 | Awareness of the legal consequences of engineering solutions | |||||
17 | An ability to describe, analyze and design digital computing and representation systems. | X | ||||
18 | An ability to use appropriate computer engineering concepts and programming languages in solving computing problems. | X |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 2 | 28 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 3 | 8 | 24 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
Total Workload | 125 |