ECTS - Analysis and Design of Algorithms for Social Sciences

Analysis and Design of Algorithms for Social Sciences (ECON551) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Analysis and Design of Algorithms for Social Sciences ECON551 3 0 0 3 5
Pre-requisite Course(s)
Course Language Turkish
Course Type N/A
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
  • Dr. Dersin Öğretim Üyesi
Course Assistants
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;
  • Upon the completion of this course, the student will be able to: Define and model the data structure with algorithms;
  • Use mathematical models and make the algorithms solve for equilibrium;
  • Analyze and critically evaluate from data driven materials;
  • Have the ability to predict the effects of changes in any kind of policy related to investigated field.
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 Lecture notes are available
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 Randomized Algorithms Lecture notes are available
8 P and NP Lecture notes are available
9 Work with NP Hard Problems Lecture notes are available
10 Work with NP Hard Problems Lecture notes are available
11 Partial Recursive function Lecture notes are available
12 Computations and Unsolvable Problems Lecture notes are available
13 Computations and Unsolvable Problems, Final Presentation of Project Lecture notes are available
14 Final Exam


Other Sources 1. Ders Notları/ Lecture notes are available

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 14 10
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 - -
Toplam 17 50
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 To compare main theories and/or approaches in political economy and make a critical evaluation of each
2 To compare main macroeconomic theories and/or approaches and make a critical evaluation of each
3 To use complementary approaches from other relevant disciplines (e.g. political science, sociology) in order to solve problems requiring scientific expertise
4 To develop the skills for establishing a micro-macro link in human and social sciences X
5 To analyze the main economic indicators and comment on them X
6 To acquire theoretical knowledge through literature survey and derive empirically testable hypothesis X
7 To be able to develop new approaches/theories for complex problems in political economy X
8 To apply critical thinking, statistical/econometric tools or other relevant quantitative and qualitative tools to new areas/problems X
9 To make a research design and carry it out within predetermined time frames X
10 To formulate and present policy recommendations based on academic research X
11 To continue learning and undertake advanced research independently X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 14 3 42
Special Course Internship
Field Work
Study Hours Out of Class 14 3 42
Presentation/Seminar Prepration 1 21 21
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 20 20
Prepration of Final Exams/Final Jury 1 25 25
Total Workload 150