ECTS - Advance Data Modelling
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) |
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N/A |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | |
Learning and Teaching Strategies | . |
Course Lecturer(s) |
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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 |
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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 |
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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 | |||||
6 | Acquiring the quantitative and/or qualitative techniques in economic analysis | |||||
7 | Improving the ability to use the modern software, hardware and/or technological devices | |||||
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) | |||
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 |