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Department of Industrial Engineering
IE 213 | Course Introduction and Application Information
| Course Name |
Computational Thinking for Operations Research
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 213
|
|
3
|
0
|
3
|
5
|
| Prerequisites | Having taken SE 113 (Enrolling in the course and having a grade other than NA or W) | |||||
| Course Language | English | |||||
| Course Type | - | |||||
| Course Level | - | |||||
| Mode of Delivery | Face-To-Face | |||||
| Teaching Methods and Techniques of the Course | Lecture/Presentation | |||||
| National Occupational Classification Code | - | |||||
| Course Coordinator | - | |||||
| Course Lecturer(s) | - | |||||
| Assistant(s) | - | |||||
| Course Objectives | This course is designed for students with basic programming experience in Python. It aims to equip students with different approaches to solving various Operations Research (OR) problems and help them confidently write programs to solve these problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning Outcomes |
The students who succeeded in this course;
|
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| Course Description | The course focuses on numerical and computational thinking for Operations Research. Toward the end of the course, students are also introduced to some basic algorithms used in Machine Learning. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Related Sustainable Development Goals |
-
|
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|
|
Core Courses |
|
| Major Area Courses |
|
|
| Supportive Courses |
|
|
| Media and Managment Skills Courses |
|
|
| Transferable Skill Courses |
|
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Required Materials | Learning Outcome |
| 1 | Review of Programming with Python | Introduction to Computation and Programming Using Python Chapter 5.4 | LO1 |
| 2 | Optimization Problems | Introduction to Computation and Programming Using Python Chapter 13 | LO1 |
| 3 | Optimization Problems | Introduction to Computation and Programming Using Python Chapter 13 | LO1 |
| 4 | Graphical Problems ve Models | Introduction to Computation and Programming Using Python Chapter 12.2 | LO1 |
| 5 | Stochastic Thinking and Random Walks | Introduction to Computation and Programming Using Python Chapters 11 ve 14 | LO2 |
| 6 | Stochastic Thinking and Random Walks | Introduction to Computation and Programming Using Python Chapters 11 ve 14 | LO2 |
| 7 | Monte Carlo Simulation | Introduction to Computation and Programming Using Python Chapters 16.4 ve 17 | LO3 |
| 8 | Midterm Exam | - | |
| 9 | Monte Carlo Simulation | Introduction to Computation and Programming Using Python Chapters 16.4 ve 17 | LO3 |
| 10 | Understanding the Experimantal Data | Introduction to Computation and Programming Using Python Chapter 18 | LO4 |
| 11 | Introduction to Machine Learning | Introduction to Computation and Programming Using Python Chapter 22 | LO5 |
| 12 | Clustering | Introduction to Computation and Programming Using Python Chapter 23 | LO5 |
| 13 | Classification | Introduction to Computation and Programming Using Python Chapter 21 | LO5 |
| 14 | Examples in Machine Learning and General Review | Introduction to Computation and Programming Using Python Chapters 21, 22, 23 | LO5 |
| 15 | General Review | - | |
| 16 | Final Exam | - |
| Course Notes/Textbooks | - |
| Suggested Readings/Materials | - |
EVALUATION SYSTEM
| Semester Activities | Number | Weighting | LO1 | LO2 | LO3 | LO4 | LO5 |
| Homework / Assignments | 4 | 30 | X | X | X | X | X |
| Midterm | 1 | 30 | X | X | X | ||
| Final Exam | 1 | 40 | X | X | X | ||
| Total | 6 | 100 |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Participation | - | - | - |
| Theoretical Course Hours | 16 | 3 | 48 |
| Laboratory / Application Hours | - | - | - |
| Study Hours Out of Class | 14 | 3 | 42 |
| Field Work | - | - | - |
| Quizzes / Studio Critiques | - | - | - |
| Portfolio | - | - | - |
| Homework / Assignments | 1 | 15 | 15 |
| Presentation / Jury | - | - | - |
| Project | - | - | - |
| Seminar / Workshop | - | - | - |
| Oral Exams | - | - | - |
| Midterms | 1 | 20 | 20 |
| Final Exam | 1 | 25 | 25 |
| Total | 150 |
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
| # | PC Sub | Program Competencies/Outcomes | * Contribution Level | ||||
| 1 | 2 | 3 | 4 | 5 | |||
| No program competency data found. | |||||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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