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) |
|---|
| (CMPE323 veya SE328) |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| 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;
|
| 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 |
|---|---|---|
| 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 |
|---|---|
| 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 |
|---|---|---|
| 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 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| 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 | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. | |||||
| 2 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose. | |||||
| 4 | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. | X | ||||
| 5 | Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. | X | ||||
| 6 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
| 7 | a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
| 8 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development. | |||||
| 9 | a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications. | |||||
| 10 | a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development. | |||||
| 11 | a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| 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 | ||