| School/Faculty/Institute | Graduate School | ||||||
| Course Code | ITC 534 | ||||||
| Course Title in English | Object-Oriented Programming (Python) | ||||||
| Course Title in Turkish | Python ile Nesne Yönelimli Programlama | ||||||
| Language of Instruction | EN | ||||||
| Type of Course | Exercise,Flipped Classroom,Lecture | ||||||
| Level of Course | Advanced | ||||||
| Semester | Spring | ||||||
| Contact Hours per Week |
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| Estimated Student Workload | 186 hours per semester | ||||||
| Number of Credits | 7.5 ECTS | ||||||
| Grading Mode | Standard Letter Grade | ||||||
| Pre-requisites | None | ||||||
| Co-requisites | None | ||||||
| Expected Prior Knowledge | None | ||||||
| Registration Restrictions | None | ||||||
| Overall Educational Objective | • To provide the advanced concepts of object-oriented programming, • To give an ability to form well-defined problem formulations for programming, • To give an ability to solve well-defined complex object-oriented programming problems by using Python programming tools, • To give an ability to design object-oriented programming systems, • To give an ability to work together with colleagues in a programming project | ||||||
| Course Description | This course aims to introduce concepts of object-oriented programming to students and help them design well-defined object-oriented programming problem formulations. Students are engaged in fundamental concepts in data structure, design patterns, GUI programming, search algorithms, and basic concepts of object-oriented programming. Then students and the instructor will apply these concepts on programming domain together. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) Define a well-defined problem formulation for a complex OOP problem 2) Design data structures 3) Solve well-defined complex problems using OOP methods and algorithms 4) Design problem solving OOP for different types of problems 5) Using design patterns for OOP 6) Develop GUI systems by Python programming language 7) Work as a team in an OOP project |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1) An ability to develop and deepen their knowledge in the field of Information Technologies at the level of expertise based on their undergraduate level qualifications. | |||||||
| 2) An ability to apply scientific and practical knowledge in statistics, computing and computer science. | |||||||
| 3) A Comprehensive knowledge of analysis and modeling methods and their limitations. | |||||||
| 4) An ability to design and apply analytical, modeling and experimental H 2 based researches, analyzes and interprets complex situations encountered in this process. | |||||||
| 5) An ability to transmit the process and results of the work of information systems systematically and clearly in written and oral form in national and international environments. | |||||||
| 6) An understanding of data collection, processing, use, interpretation and social, scientific and ethical values in all professional and professional activities. | |||||||
| 7) An ability to take a leadership position in multi-disciplinary teams, develop information-based solution approaches in complex situations and to take responsibility. | |||||||
| 8) An understanding of the impact of engineering solutions in a global, economic, environmental, and societal context. | |||||||
| 9) An ability to communicate verbally and in writing in English at least at the level of B2 of CEFR. | |||||||
| 10) An understanding the social and environmental aspects of IT applications. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to develop and deepen their knowledge in the field of Information Technologies at the level of expertise based on their undergraduate level qualifications. | N | |
| 2) | An ability to apply scientific and practical knowledge in statistics, computing and computer science. | N | |
| 3) | A Comprehensive knowledge of analysis and modeling methods and their limitations. | N | |
| 4) | An ability to design and apply analytical, modeling and experimental H 2 based researches, analyzes and interprets complex situations encountered in this process. | N | |
| 5) | An ability to transmit the process and results of the work of information systems systematically and clearly in written and oral form in national and international environments. | N | |
| 6) | An understanding of data collection, processing, use, interpretation and social, scientific and ethical values in all professional and professional activities. | N | |
| 7) | An ability to take a leadership position in multi-disciplinary teams, develop information-based solution approaches in complex situations and to take responsibility. | N | |
| 8) | An understanding of the impact of engineering solutions in a global, economic, environmental, and societal context. | N | |
| 9) | An ability to communicate verbally and in writing in English at least at the level of B2 of CEFR. | N | |
| 10) | An understanding the social and environmental aspects of IT applications. | N |
| Prepared by and Date | ŞENİZ DEMİR , February 2024 |
| Course Coordinator | ŞENİZ DEMİR |
| Semester | Spring |
| Name of Instructor | Assoc. Prof. Dr. ŞENİZ DEMİR |
| Week | Subject |
| 1) | Variables, Decision Structures, Repetition Structures |
| 2) | Functions |
| 3) | Lists, Tuples |
| 4) | Dictionaries, Sets |
| 4) | Dictionaries, Sets |
| 5) | Iterations, Comprehensions |
| 6) | Classes |
| 7) | Encapsulation |
| 8) | Inheritance |
| 9) | Overloading |
| 10) | Polymorphism |
| 11) | Object-oriented Design and Algorithms I |
| 12) | Object-oriented Design and Algorithms II |
| 13) | Advanced Class Topics I |
| 14) | Advanced Class Topics II |
| 15) | Final Examination Period |
| 16) | Final Examination Period |
| Required/Recommended Readings | Learning Python, Mark Lutz. | |||||||||
| Teaching Methods | Flipped classroom. Students work for programming assignments. | |||||||||
| Homework and Projects | Programming assignments | |||||||||
| Laboratory Work | None | |||||||||
| Computer Use | Required | |||||||||
| Other Activities | None | |||||||||
| Assessment Methods |
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| Course Administration |
demirse@mef.edu.tr 536 Instructor’s office: 5th floor Phone number: 0 212 395 37 96 Office hours: After the lecture hours. E-mail address: demirse@mef.edu.tr |
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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 5 | 1 | 98 | ||
| Homework Assignments | 4 | 0 | 22 | 88 | |||
| Total Workload | 186 | ||||||
| Total Workload/25 | 7.4 | ||||||
| ECTS | 7.5 | ||||||