School/Faculty/Institute | Faculty of Engineering | ||||||
Course Code | COMP 303 | ||||||
Course Title in English | Analysis of Algorithms | ||||||
Course Title in Turkish | Algoritma Analizi | ||||||
Language of Instruction | EN | ||||||
Type of Course | Flipped Classroom | ||||||
Level of Course | Introductory | ||||||
Semester | Fall | ||||||
Contact Hours per Week |
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Estimated Student Workload | 158 hours per semester | ||||||
Number of Credits | 6 ECTS | ||||||
Grading Mode | Standard Letter Grade | ||||||
Pre-requisites |
COMP 201 - Data Structures and Algorithms |
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Expected Prior Knowledge | Object Oriented Programming, Data Structures | ||||||
Co-requisites | None | ||||||
Registration Restrictions | Only Undergraduate Students | ||||||
Overall Educational Objective | To evaluate the efficiency of algorithms used to solve a computational problem. | ||||||
Course Description | This course provides a comprehensive introduction to some fundamental aspects of Analysis of Algorithms. The following topics are covered: Introduction, mathematical foundations; asymptotic analysis; recurrences; sorting algorithms, merge sort, heap sort; randomized algorithms, Hashing, searching, Binary search Trees, 2-3 Tress, Red and Black trees , Binomial Heaps; Fibonacci Heaps Given a computational problem, we want to (a) find an algorithm to solve the problem, (b) prove that the algorithm solves the problem correctly, (c) prove that we cannot solve the problem any faster, and (d) implement the algorithm. The course focuses on these topics by studying useful algorithmic design techniques and methods for analyzing algorithms. | ||||||
Course Description in Turkish | Bu derste; Algoritma Analizinin temel kavramları şu konu başlıklar altında kapsamlı bir şekilde incelenmektedir: Giriş, Matematiksel temeller, asimptotik analiz, yineleme, sıralama algoritmaları, birleştirme sıralama, yığın sıralama, rastsal algoritmalar, özütleme, arama, ikili arama ağaçları, 2-3 Ağaçları, Kırmızı-Siyah ağaçlar, İkiterimli yığınlar, Fibonacci yığınları |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) analyze the performance of algorithms by using asymptotic notation; 2) solve recurrences; 3) describe and compare sorting algorithms 4) identify complicated data structures such as Hashing, B-trees, Red-Black trees, heap structures; 5) analyze graphs ; 6) design and implement efficient algorithms to solve a computational problem; 7) analyze and interpret algorithms to solve a computational problem; |
Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|
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. |
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 | MUHİTTİN GÖKMEN , December 2018 |
Course Coordinator | YASSINE DRIAS |
Semester | Fall |
Name of Instructor | Prof. Dr. MUHİTTİN GÖKMEN |
Week | Subject |
1) | Introduction |
2) | Asymptotic Analysis |
3) | Recurrences |
4) | Probabilistic Analysis and Randomized Algorithms |
5) | Heap Sort and Merge sort |
6) | Quicksort, sorting in linear time |
7) | Medians and Order Statistics |
8) | Elementary Data Structures and overview |
9) | Hash tables |
10) | Hash functions |
11) | Binary search tree, 2-3 trees |
12) | 2-3-4 trees, Red-Black trees |
13) | B-trees |
14) | Graphs |
15) | Final Exam/Project/Presentation |
16) | Final Exam/Project/Presentation |
Required/Recommended Readings | Introduction to Algorithms , Third Edition, T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein MIT Press, 2009, ISBN 978-0-262-03384-8 | |||||||||||||||
Teaching Methods | Lecturing and exercises in the classroom with computers. In-class exercises and 3 Projects will be carried out by students | |||||||||||||||
Homework and Projects | In-class exercises, Projects | |||||||||||||||
Laboratory Work | Programming exercises | |||||||||||||||
Computer Use | For Programming | |||||||||||||||
Other Activities | ||||||||||||||||
Assessment Methods |
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Course Administration |
gokmenm@mef.edu.tr 0 212 395 36 26 Instructor’s office and phone number, office hours, email address: To be announced -Office: 5th Floor, #18 -Phone number: 0 212 395 36 26 - Email address: gokmenm@mef.edu.tr Rules for attendance: Minimum of 70% attendance required. Missing a quiz: Provided that proper documents of excuse are presented, each missed quiz by the student will be given a grade which is equal to the average of all of the other quizzes. No make-up will be given. Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations |
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 | 3 | 1 | 70 | ||
Project | 1 | 30 | 2 | 2 | 34 | ||
Quiz(zes) | 6 | 4 | 1 | 30 | |||
Midterm(s) | 2 | 10 | 2 | 24 | |||
Total Workload | 158 | ||||||
Total Workload/25 | 6.3 | ||||||
ECTS | 6 |