ECTS - Analysis and Design of Algorithms
Analysis and Design of Algorithms (ECON381) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Analysis and Design of Algorithms | ECON381 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| 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. |
| Course Lecturer(s) |
|
| Course Objectives | This course provides an understanding of the application of software technologies that enables users to make better and faster decisions based on big data features. Students will learn the principles and best practices for how to use big data in order to support fact-based decision-making. Emphasis will be given to applications in various data which has big data facilities. Therefore, in this course, the algorithms which are given in the class targeted the big data facilities in order to teach student this structure. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Review of algorithm analysis; divide and conquer algorithms; graphs; dynamic programming; greedy algorithms; randomized algorithms; P and NP; approximate algorithms for NP-hard problems or polynomial algorithms for subproblems of NP-hard problems; partial recursive functions; computations and undecidable problems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Search and Sorting | |
| 2 | Divide and Conquer Algorithms | Lecture notes are available |
| 3 | Graphs, Project Proposal | Lecture notes are available |
| 4 | Dynamic Programming | Lecture notes are available |
| 5 | Dynamic Programming | Lecture notes are available |
| 6 | Greedy Algorithms | Lecture notes are available |
| 7 | Midterm Exam | Lecture notes are available |
| 8 | Rastgele Algoritmalar | Lecture notes are available |
| 9 | P and NP | Lecture notes are available |
| 10 | Work with NP Hard Problems | Lecture notes are available |
| 11 | Work with NP Hard Problems | Lecture notes are available |
| 12 | Partial Recursive function. | Lecture notes are available |
| 13 | Computations and Unsolvable Problems | Lecture notes are available |
| 14 | Computations and Unsolvable Problems, Final Presentation of Project, Final | Lecture notes are available |
| 15 | Computations and Unsolvable Problems, Final Presentation of Project, Final | Lecture notes are available |
| 16 | Fınal Exam |
Sources
| Course Book | 1. Introdution to Algoritms, Thomas H. Cormen, Charles E. Leiserson, Ron Rivest, Clifford Stein |
|---|---|
| Other Sources | 2. Ders Notları |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 15 | 1 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | 2 | 20 |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 20 |
| Final Exam/Final Jury | 1 | 50 |
| Toplam | 19 | 91 |
| Percentage of Semester Work | |
|---|---|
| Percentage of Final Work | 100 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| 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 | Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics | |||||
| 2 | Acquiring the skills of macro level economic analysis | |||||
| 3 | Acquiring the skills of micro level economic analysis | |||||
| 4 | Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level | |||||
| 5 | Learning different approaches on economic and related issues | X | ||||
| 6 | Acquiring the quantitative and/or qualitative techniques in economic analysis | X | ||||
| 7 | Improving the ability to use the modern software, hardware and/or technological devices | X | ||||
| 8 | Developing intra-disciplinary and inter-disciplinary team work skills | |||||
| 9 | Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning | |||||
| 10 | Adopting work ethic and social responsibility | |||||
| 11 | Developing the skills of communication. | |||||
| 12 | Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 3 | 48 |
| Presentation/Seminar Prepration | 1 | 21 | 21 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 142 | ||