ECTS - Algorithms
Algorithms (MCS401) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Algorithms | MCS401 | Elective Courses | 2 | 2 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Drill and Practice, Team/Group. |
| Course Lecturer(s) |
|
| Course Objectives | The objective of this course is to introduce the importance of algorithms in computing. Students will learn variety of different algorithmic design and analysis techniques and how to measure the complexity of algorithms. The reason for teaching well known and basic algorithms in this course is not only to show how these particular problems are solved, but also to give the students the practice and the skills required in developing solutions for new problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Design and Analysis of Algorithms, O,o,ω,Ω,Θ Notations, Lower and Upper Bound Theory, Divide and Conquer Algorithms, Recurrences, Dynamic Programming, Complexity of Sorting and Searching Algorithms, Greedy Algorithms, Greedy Algorithms vs. Dynamic Programming, Elementary Graph Algorithms, NP-Completeness |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Analysis and Design of Algorithms, Basics | pp. 5-14 |
| 2 | Growth of Functions: Asymptotic Notations O,o,ω,Ω,Θ | pp. 41-56 |
| 3 | Proof of Correctness of Algorithms | pp. 15-27 |
| 4 | Divide and Conquer Algorithms | pp. 28-33 |
| 5 | Recurrences | pp. 63-76 |
| 6 | Sorting, Insertion Sort , Quicksort | pp. 145-163 |
| 7 | Merge Sort , Bubble Sort , Linear Sort Algorithms: Counting Sort, Radix Sort | pp. 165-174 |
| 8 | Dynamic Programming, Matrix Multiplication Order | pp. 331-348 |
| 9 | Longest Common Subsequence, Linear Search and Binary Search | pp. 350-356 |
| 10 | Graph algorithms, Shortest Path Algorithms | pp. 595-607 |
| 11 | Depth First Search and Breadth First Search | pp. 527-549 |
| 12 | Greedy Approach. Kruskal's Algorithm | pp. 562-577 |
| 13 | P, NP and NP-complete Problems | pp. 966-995 |
| 14 | Basic Cryptographic Algorithms, RSA, Review | pp. 881-896 |
| 15 | Review | |
| 16 | Final Exam |
Sources
| Course Book | 1. Introduction to Algorithms (Second Edition), Thomas Cormen, Charles Leiserson, Ronald Rivest and Clifford Stein, MIT Press, 2001 |
|---|---|
| Other Sources | 2. Algorithms in C++, 3rd Edition, Part 1-4, Robert Sedgewick, Addison Wesley, 1998, ISBN, 0-201-35088-2. |
| 3. Foundations of Algorithms Using C++ Pseudocode, 3rd Edition, Jones And Bartlett Publishers 2004. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 5 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 8 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | X |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors. | X | ||||
| 2 | Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices. | X | ||||
| 3 | Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills. | X | ||||
| 4 | Acquires analytical thinking and uses time effectively in the process of deduction | X | ||||
| 5 | Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively. | X | ||||
| 6 | Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes. | X | ||||
| 7 | Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning. | X | ||||
| 8 | Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team. | X | ||||
| 9 | Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields. | X | ||||
| 10 | Has the ability to communicate ideas with peers supported by qualitative and quantitative data. | X | ||||
| 11 | Has professional and ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | |||
| Laboratory | 16 | 2 | 32 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 5 | 6 | 30 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 12 | 24 |
| Prepration of Final Exams/Final Jury | 1 | 18 | 18 |
| Total Workload | 146 | ||