TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| COMPUTER ENGINEERING PR. (ENGLISH) | |
| Code | CEN304 |
| Name | Artificial Intelligence Systems |
| Term | 2015-2016 Academic Year |
| Semester | 6. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Üniversite Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
Doç. Dr. MUSTAFA ORAL
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Knowledge representation. Search and intuitive programming. Logic and logic programming. Applications of artificial intelligence: Problem solving, games and puzzles, expert systems, planning, learning, pattern recognition, natural language understanding.
Course Content
Representation of knowledge. Search and heuristic programming. Logic and logic programming. Application areas of artificial intelligence: Problem solving, games and puzzles, expert systems, planning, learning, vision, and natural language understanding. Exercises in an artificial intelligence language
Course Precondition
Yok
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learnes Knowldege and Reasoning concepts Makes planning Grasps Learning concept To learn the basics of creating human and animal thinking systems based software and machines. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has capability in the fields of mathematics, science and computer that form the foundations of engineering | |
| PLO02 | - | Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, | |
| PLO03 | - | Analyzes a system, its component, or process and designs under realistic constraints to meet the desired requirements,gains the ability to apply the methods of modern design accordingly. | |
| PLO04 | - | Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. | |
| PLO05 | - | Ability to design and to conduct experiments, to collect data, to analyze and to interpret results | |
| PLO06 | - | Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence | |
| PLO07 | - | Can access information,gains the ability to do resource research and uses information resources | |
| PLO08 | - | Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability | |
| PLO09 | - | Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language | |
| PLO10 | - | Professional and ethical responsibility, | |
| PLO11 | - | Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications, | |
| PLO12 | - | Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Artificial Intelligence | Reading the lecture notes | |
| 2 | Intelligent Agents | Reading the lecture notes | |
| 3 | Problem Solving and Search | Reading the lecture notes | |
| 4 | Heuristic Problem Examples | Reading the lecture notes | |
| 5 | Pattern Recognition | Reading the lecture notes | |
| 6 | Expert Systems | Reading the lecture notes | |
| 7 | Learning and Neural Networks | Reading the lecture notes | |
| 8 | Midterm Exam | Reading the lecture notes | |
| 9 | Fuzzy Logic | Reading the lecture notes | |
| 10 | Evolutionary Methods | Reading the lecture notes | |
| 11 | Genetic Algorithm | Reading the lecture notes | |
| 12 | Ant Colony Algorithm | Reading the lecture notes | |
| 13 | Project Presentations | Reading the lecture notes | |
| 14 | Project Presentations | Reading the lecture notes | |
| 15 | Problem Solving | Reading the lecture notes | |
| 16 | Final exam | Reading the lecture notes | |
| 17 | Final exam | Reading the lecture notes |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | -20 |
| 1. Midterm Exam | 100 | -20 |
| General Assessment | ||
| Midterm / Year Total | 200 | -20 |
| 1. Final Exam | - | 60 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 13 | 3 | 39 |
| Out of Class Study (Preliminary Work, Practice) | 13 | 3 | 39 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 15 | 15 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 15 | 15 |
| Total Workload (Hour) | 123 | ||
| Total Workload / 25 (h) | 4,92 | ||
| ECTS | 6 ECTS | ||