Data Science (Master) (with Thesis) (English) | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code: | DATS5290 | ||||
Course Name: | Thesis 2 | ||||
Semester: | Spring | ||||
Course Credits: |
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Language of instruction: | English | ||||
Course Condition: | |||||
Does the Course Require Work Experience?: | No | ||||
Type of course: | Compulsory Courses | ||||
Course Level: |
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Mode of Delivery: | E-Learning | ||||
Course Coordinator: | Doç. Dr. ŞEBNEM ÖZDEMİR | ||||
Course Lecturer(s): |
Doç. Dr. ŞEBNEM ÖZDEMİR |
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Course Assistants: |
Course Objectives: | It aims to develop students' academic research skills, to conduct an independent and original research, to manage this process within the framework of ethical rules and to increase their academic communication skills by producing a scientific written work. The main objective of this course is to enable students to identify a problem specific to their chosen field, to gain in-depth knowledge about this problem, to select and apply appropriate research methods and to produce original results with their own analysis. |
Course Content: | 1. Examination and application of research methodologies. 2. Literature review techniques and information management. 3. Scientific data analysis, modeling and interpretation. 4. Academic writing techniques and ethical rules. 5. Thesis writing process and presentation techniques. |
The students who have succeeded in this course;
1) 1. Mastery of independent research execution. 2) 2. Capability to select and apply necessary research methods. 3) 3. Proficiency in academic writing and presentation skills. 4) 4. Adherence to research ethics and copyright principles. 5) 5. Ability to analyze findings and produce a scientific written report. |
Week | Subject | Related Preparation |
1) | Thesis Study | |
2) | Thesis Study | |
3) | Thesis Study | |
4) | Thesis Study | |
5) | Thesis Study | |
6) | Thesis Study | |
7) | Thesis Study | |
8) | Thesis Study | |
9) | Thesis Study | |
10) | Thesis Study | |
11) | Thesis Study | |
12) | Thesis Study | |
13) | Thesis Study | |
14) | Thesis Study |
Course Notes / Textbooks: | The Craft of Research, Fourth Edition (Chicago Guides to Writing, Editing, and Publishing) Fourth Edition by Wayne C. Booth (Author), Gregory G. Colomb (Author), Joseph M. Williams (Author), Joseph Bizup (Author) |
References: | The Craft of Research, Fourth Edition (Chicago Guides to Writing, Editing, and Publishing) Fourth Edition by Wayne C. Booth (Author), Gregory G. Colomb (Author), Joseph M. Williams (Author), Joseph Bizup (Author) |
Course Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
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Program Outcomes | |||||
1) Students who successfully complete this program, Knows the scope of technical applications of data science and the tools that can be used. | 3 | 3 | 3 | 3 | 3 |
2) Students who successfully complete this program, Knows the effects of application results on society-culture-law. | 3 | 3 | 3 | 3 | 3 |
3) Students who complete this program; Recognize the mathematics and code in application processes | 3 | 3 | 3 | 3 | 3 |
4) Students who complete this program; Explain the effects of the processes in data science on the output and the individual | 3 | 3 | 3 | 3 | 3 |
5) Students who successfully complete this program, Understands the insight-foresight and foresight created by data science as a whole in the face of a certain discipline/case. | 3 | 3 | 3 | 3 | 3 |
No Effect | 1 Lowest | 2 Average | 3 Highest |
Program Outcomes | Level of Contribution | |
1) | Students who successfully complete this program, Knows the scope of technical applications of data science and the tools that can be used. | 3 |
2) | Students who successfully complete this program, Knows the effects of application results on society-culture-law. | 3 |
3) | Students who complete this program; Recognize the mathematics and code in application processes | 3 |
4) | Students who complete this program; Explain the effects of the processes in data science on the output and the individual | 3 |
5) | Students who successfully complete this program, Understands the insight-foresight and foresight created by data science as a whole in the face of a certain discipline/case. | 3 |
Semester Requirements | Number of Activities | Level of Contribution |
Presentation | 1 | % 100 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 100 | |
PERCENTAGE OF FINAL WORK | % | |
total | % 100 |
Activities | Number of Activities | Workload |
Presentations / Seminar | 14 | 740 |
Total Workload | 740 |