Information Package / Course Catalogue
| Psychology | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Engineering | ||||
| Course Code | COMP 201 | ||||
| Course Title in English | Data Structures and Algorithms | ||||
| Course Title in Turkish | Veri Yapıları ve Algoritmalar | ||||
| Language of Instruction | EN | ||||
| Type of Course | Exercise,Flipped Classroom,Lecture | ||||
| Level of Course | Introductory | ||||
| Semester | Fall | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 152 hours per semester | ||||
| Number of Credits | 6 ECTS | ||||
| Grading Mode | Standard Letter Grade | ||||
| Pre-requisites |
COMP 109 - Computer Programming (JAVA) |
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| Expected Prior Knowledge | Basic object-oriented programming knowledge | ||||
| Co-requisites | None | ||||
| Registration Restrictions | Only Undergraduate Students | ||||
| Overall Educational Objective | To learn fundamentals of data structures and how to design and implement data structures to solve basic engineering problems in Java programming language. | ||||
| Course Description | This course covers the fundamentals of data structures and algorithms such as lists, stacks, queues, heaps, trees, hashing, sorting algorithms, and application of these concepts using Java programming language. | ||||
| Course Description in Turkish | Bu ders veri yapıları ve algoritmaların temellerini içermektedir. Dersin içeriği listeler, yığınlar, sıralar, kümeler, karmalar, ve sıralama algoritmaları ve bunların Java programlama dili kullanılarak uygulanmasıdır. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) Comprehend basic data structure concepts. 2) Design algorithms using data structures. 3) Implement data structures to solve engineering problems. 4) Analyze and report the results of implemented solution. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
| 1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | ||||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | ||||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | ||||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | ||||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | ||||
| 6) Internalization and dissemination of professional ethical standards. | ||||
| 7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | ||||
| 8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | ||||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | ||||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | ||||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | ||||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | ||||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
| 6) | Internalization and dissemination of professional ethical standards. | N | |
| 7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
| 8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | , November 2023 |
| Course Coordinator | YASSINE DRIAS |
| Semester | Fall |
| Name of Instructor | Asst. Prof. Dr. YASSINE DRIAS |
Course Contents
| Week | Subject |
| 1) | Introduction to Data Structures |
| 2) | Abstract Classes and Interfaces |
| 3) | Generics |
| 4) | Lists (Part 1) |
| 5) | Lists (Part 2) |
| 6) | Stacks |
| 7) | Queues |
| 8) | Algorithmic complexity |
| 9) | Heaps and Priority Queues |
| 10) | Hashing |
| 11) | Recursion |
| 12) | Trees (Part 1) |
| 13) | Trees (Part 2) |
| 14) | Algorithm design using data structures |
| 15) | Final Examination Period |
| 16) | Final Examination Period |
| Required/Recommended Readings | Intro. to Java Programming: Comprehensive Ed. (11th Ed., Pearson, 2019), Daniel Liang. Data Structures and Algorithms in Java, Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, Adison Wesley 6th Edition | |||||||||||||||
| Teaching Methods | Flipped classroom. Students work individually for assignments. | |||||||||||||||
| Homework and Projects | Assignments | |||||||||||||||
| Laboratory Work | Laboratory study | |||||||||||||||
| Computer Use | Required | |||||||||||||||
| Other Activities | none | |||||||||||||||
| Assessment Methods |
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| Course Administration |
driasy@mef.edu.tr 0 212 395 37 45 Instructor’s office: 5th floor Phone number: 0 212 395 37 45 Office hours: After the lecture hours. E-mail address: driasy@mef.edu.tr Rules for attendance: No attendance required. Statement on plagiarism: YÖK Regulations |
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ECTS Student Workload Estimation
| 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 | 84 | |||
| Project | 4 | 1 | 16 | 68 | |||
| Total Workload | 152 | ||||||
| Total Workload/25 | 6.1 | ||||||
| ECTS | 6 | ||||||