| INFORMATION TECHNOLOGIES (ENGLISH, NON-THESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| CMP5103 | Artificial Intelligence | Fall | 3 | 0 | 3 | 8 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi TEVFİK AYTEKİN |
| Course Lecturer(s): |
Prof. Dr. NAFİZ ARICA |
| Course Objectives: | The objective of this course is to give the student the ability to apply artificial intelligence techniques, including search heuristics, knowledge representation, planning, reasoning and learning to various problems. |
|
The students who have succeeded in this course; I. Be able to solve problems by applying a suitable search method. II. Be able to implement minimax search and alpha-beta pruning in game playing. III. Be able to use logical formalisms in modeling. IV. Be able to apply supervised learning techniques to a given problem. V. Be able to apply unsupervised learning techniques to a given problem. VI. Be able to use the basic techniques in natural language processing. |
| introduction; uninformed search strategies; informed (heuristic) search strategies; adversarial search; propositional logic; predicate logic; supervised learning techniques; unsupervised learning techniques; natural language processing. |
| Week | Subject | Related Preparation | |
| 1) | Introduction | ||
| 2) | Uninformed Search Strategies | ||
| 3) | Uninformed Search Strategies | ||
| 4) | Informed (Heuristic) Search Strategies | ||
| 5) | Informed (Heuristic) Search Strategies | ||
| 6) | Adversarial Search | ||
| 7) | Propositional Logic | ||
| 8) | Predicate logic | ||
| 9) | Supervised Learning Techniques | ||
| 10) | Supervised Learning Teknileri | ||
| 11) | Unsupervised Learning Techniques | ||
| 12) | Unsupervised Learning Techniques | ||
| 13) | Natural Language Processing | ||
| 14) | Natural Language Processing | ||
| 15) | Final Exam | ||
| Course Notes: | Russell, S., Norvig, P., Artificial Intelligence: A Modern Approach, (3rd edition), 2009. Giarratano, J.C., Riley, G.D., Expert Systems: Principles and Programming, (4th edition), 2004. |
| References: |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | % 0 | |
| Laboratory | % 0 | |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | % 0 | |
| Homework Assignments | % 0 | |
| Presentation | 1 | % 10 |
| Project | 1 | % 50 |
| Seminar | % 0 | |
| Midterms | % 0 | |
| Preliminary Jury | % 0 | |
| Final | 1 | % 40 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 10 | |
| PERCENTAGE OF FINAL WORK | % 90 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentations / Seminar | 0 | 0 | 0 |
| Project | 1 | 42 | 42 |
| Homework Assignments | 7 | 8 | 56 |
| Quizzes | 0 | 0 | 0 |
| Preliminary Jury | 0 | ||
| Midterms | 0 | 0 | 0 |
| Paper Submission | 0 | ||
| Jury | 0 | ||
| Final | 1 | 12 | 12 |
| Total Workload | 194 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Uses basic Software Engineering knowledge and competencies. | |
| 2) | Applies the software development ability that is necessary for software engineering applications. | |
| 3) | Uses data structures and applies information about algorithm development. | |
| 4) | Develops system programs on operating systems. | |
| 5) | Defines computer organization, design and architectures. | |
| 6) | Creates the structure of computer networks and network security. | |
| 7) | Uses business intelligence, data mining and data analysis tools, applies techniques about them. | |
| 8) | Develops database applications and WEB based programs. | |
| 9) | Defines, analyzes, designs and manages information technologies projects. | |
| 10) | Uses and develops technology-based environments and tools in education. | |
| 11) | Detects, identifies and solves information technology needs of the business environment. | |
| 12) | Uses the capabilities of information technologies within the rules of professional responsibility and ethics. |