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- Software Engineering
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11111
COURSE INTRODUCTION AND APPLICATION INFORMATION
se.cs.ieu.edu.tr
| Course Name | |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| Fall/Spring |
| Prerequisites | None | |||||
| Course Language | ||||||
| Course Type | Elective | |||||
| Course Level | - | |||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | ||||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | |
| Learning Outcomes | The students who succeeded in this course;
|
| Course Description |
|
| Core Courses | |
| Major Area Courses | ||
| Supportive Courses | X | |
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Required Materials |
| 1 | Introduction to AI Introduction to Expert Systems | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach Ch 1Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 2 | Introduction to AI • Intelligent Agents Examples to AI Languages • Introduction to Common Lisp • Introduction to Prolog | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 3 | Problem Solving by Search I • Introduction to Search • Informed Search • Uninformed Search • Constraint Satisfaction Problems | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 4 | Problem Solving by Search II • Introduction to Search • Informed Search • Uninformed Search • Constraint Satisfaction Problems | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 5 | Problem Solving by Search III • Introduction to Search • Informed Search • Uninformed Search • Constraint Satisfaction Problems | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 6 | Expert Systems I | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 7 | Expert Systems II | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 8 | Expert Systems III | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 9 | MIDTERM | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 10 | AI: Language Processing | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 11 | AI: Machine Learning I | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 12 | AI: Machine Learning II | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 13 | AI: Information Retrieval | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 14 | Review of the Semester | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| 15 | Review of the Semester | |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010, ISBN10: 0132124114. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition |
| Suggested Readings/Materials | Internet |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | 1 | 10 |
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | 5 | 20 |
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | 2 | 40 |
| Project | ||
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 1 | 30 |
| Final Exam | 1 | |
| Total |
| Weighting of Semester Activities on the Final Grade | 10 | 100 |
| Weighting of End-of-Semester Activities on the Final Grade | ||
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
| Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
| Study Hours Out of Class | 15 | 4 | |
| Field Work | |||
| Quizzes / Studio Critiques | 5 | 8 | |
| Portfolio | |||
| Homework / Assignments | |||
| Presentation / Jury | 2 | 20 | |
| Project | |||
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 1 | 37 | |
| Final Exams | 1 | ||
| Total | 225 |
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | Be able to define problems in real life by identifying functional and nonfunctional requirements that the software is to execute | X | ||||
| 2 | Be able to design and analyze software at component, subsystem, and software architecture level | X | ||||
| 3 | Be able to develop software by coding, verifying, doing unit testing and debugging | X | ||||
| 4 | Be able to verify software by testing its behaviour, execution conditions, and expected results | X | ||||
| 5 | Be able to maintain software due to working environment changes, new user demands and the emergence of software errors that occur during operation | X | ||||
| 6 | Be able to monitor and control changes in the software, the integration of software with other software systems, and plan to release software versions systematically | X | ||||
| 7 | To have knowledge in the area of software requirements understanding, process planning, output specification, resource planning, risk management and quality planning | X | ||||
| 8 | Be able to identify, evaluate, measure and manage changes in software development by applying software engineering processes | X | ||||
| 9 | Be able to use various tools and methods to do the software requirements, design, development, testing and maintenance | X | ||||
| 10 | To have knowledge of basic quality metrics, software life cycle processes, software quality, quality model characteristics, and be able to use them to develop, verify and test software | X | ||||
| 11 | To have knowledge in other disciplines that have common boundaries with software engineering such as computer engineering, management, mathematics, project management, quality management, software ergonomics and systems engineering | X | ||||
| 12 | Be able to grasp software engineering culture and concept of ethics, and have the basic information of applying them in the software engineering | X | ||||
| 13 | Be able to use a foreign language to follow related field publications and communicate with colleagues | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest