Advance Data Modelling (IKT481) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Advance Data Modelling IKT481 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
Learning and Teaching Strategies .
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives
Course Learning Outcomes The students who succeeded in this course;
Course Content The main contents are; statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of policies and programs. Students will learn the principles and best practices for how to use data in order to support fact-based decision-making. Emphasis will be given to applications in various data which has big data facilities.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation

Sources

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury - -
Final Exam/Final Jury - -
Toplam 0 0
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 They acquire the skills to understand, explain, and use the basic concepts and methods of economics.
2 Acquires macro-economic analysis skills.
3 Acquire microeconomic analysis skills.
4 Understands the formulation and implementation of economic policies at local, national, regional and/or global levels.
5 Learn different approaches to the economy and economic issues.
6 Learn qualitative and quantitative research techniques in economic analysis.
7 Improving the ability to use modern software, hardware and/or other technological tools.
8 Develops intra-disciplinary and inter-disciplinary team work skills.
9 Contributes to open-mindedness by encouraging critical analysis, discussion, and/or lifelong learning.
10 Develops a sense of work ethics and social responsibility.
11 Develops communication skills.
12 Improving the ability to effectively apply knowledge and skills in at least one of the following areas: Economic policy, public policy, international economic relations, industrial relations, monetary and financial relations

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury
Total Workload 0