ECTS - Knowledge Engineering
Knowledge Engineering (CMPE465) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Knowledge Engineering | CMPE465 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| 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) |
|
| Course Objectives | This course is designed to provide the skills needed to develop computer programs that contain large amount of knowledge, rules and reasoning mechanisms to provide solutions to real-world problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Knowledge representation methods: rule-based, graph-based, logic-based methods, introduction to Prolog, knowledge acquisition, expert systems, ontology, semantic web, introduction to machine learning. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction | Chapter 1 (main text) |
| 2 | Knowledge Representation | Chapter 1 |
| 3 | Rule-Based Knowledge Representation | Chapter 7 |
| 4 | Graph-Based Knowledge Representation | Chapter 8 |
| 5 | Semantic Nets | Lecture Notes |
| 6 | Frames | Chapter 8 |
| 7 | First-Order Logic | Chapter 2 |
| 8 | Introduction to Prolog - I | (Other sources 3) |
| 9 | Introduction to Prolog - II | (Other sources 3) |
| 10 | Knowledge Acquisition | (Other sources 2) |
| 11 | Expert Systems | (Other sources 2) |
| 12 | Semantic Web | (Other sources 4) |
| 13 | Ontology | (Other sources 4) |
| 14 | Machine Learning | Lecture Notes |
Sources
| Course Book | 1. Knowledge Representation and Reasoning, R.J.Brachman and H.J.Levesque, Morgan Kaufmann, 2004. |
|---|---|
| Other Sources | 2. 1. Knowledge Representation: Logical, Philosophical, and Computational Foundations, John F. Sowa, Brooks/Cole, Thomson Learning, 2000. |
| 3. 2. Introduction to Expert Systems, Peter Jackson, Addison-Wesley, 1999, | |
| 4. 3. Programming in Prolog, W.F.Cloksin, C.S. Mellish, Springer-Verlag, 1981. | |
| 5. 4. W3C Semantic Web Activity, www.w3.org | |
| 6. 5. Reasoning about Knowledge, R. Fagin, J.Y.Halpern, Y. Moses, and M.Y.Vardi, MIT Press, 2003. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 1 | 30 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 3 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| 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 | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Has adequate knowledge in mathematics, science, and computer engineering-specific subjects; uses theoretical and practical knowledge in these areas to solve complex engineering problems. | X | ||||
| 2 | Identifies, defines, formulates, and solves complex engineering problems; selects and applies appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Designs a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; applies modern design methods for this purpose. | X | ||||
| 4 | Develops, selects, and uses modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; uses information technologies effectively. | X | ||||
| 5 | Designs experiments, conducts experiments, collects data, analyzes and interprets results for the investigation of complex engineering problems or research topics specific to the discipline of computer engineering. | X | ||||
| 6 | Works effectively in disciplinary and multidisciplinary teams; gains the ability to work individually. | X | ||||
| 7 | Communicates effectively in Turkish, both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. | X | ||||
| 8 | Knows at least one foreign language; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. | |||||
| 9 | Has awareness of the necessity of lifelong learning; accesses information, follows developments in science and technology, and continuously improves oneself. | |||||
| 10 | Acts in accordance with ethical principles and has awareness of professional and ethical responsibility. | |||||
| 11 | Has knowledge about the standards used in computer engineering applications. | |||||
| 12 | Has knowledge about workplace practices such as project management, risk management, and change management. | |||||
| 13 | Gains awareness about entrepreneurship and innovation. | |||||
| 14 | Has knowledge about sustainable development. | |||||
| 15 | Has knowledge about the health, environmental, and safety impacts of computer engineering applications in universal and societal dimensions and the contemporary issues reflected in the field of engineering. | |||||
| 16 | Gains awareness of the legal consequences of engineering solutions. | |||||
| 17 | Analyzes, designs, and expresses numerical computation and digital representation systems. | |||||
| 18 | Uses programming languages and appropriate computer engineering concepts to solve computational problems. | X | ||||
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 | 16 | 2 | 32 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 15 | 15 |
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 15 | 15 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 125 | ||