ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| Data Science (Master) (with Thesis) (English) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
Course Introduction and Application Information
| Course Code: | DATS5189 | ||||
| Course Name: | Seminar | ||||
| 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. OKAN YAŞAR |
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| Course Assistants: |
Course Objective and Content
| Course Objectives: | The main objective of this seminar course is to deeply engage students with the current trends and research within the field of Management Information Systems. This will be achieved by critically analyzing academic literature, exploring case studies, and understanding the implications of emerging technologies in the business world. The course will also prepare students to conduct their own research and enhance their ability to effectively communicate their insights and findings both orally and in writing. By the end of the course, students will be able to contribute to the field of MIS through informed discussion and original research. |
| Course Content: | 1. Advanced topics in Management Information Systems including recent research and case studies. 2. Critical analysis and discussion of scholarly articles and professional publications in the field. 3. Presentation and critique of emerging technologies impacting business strategies. 4. Designing and conducting original research in the field of Management Information Systems. 5. Development of communication skills through presentations and written assignments. |
Learning Outcomes
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The students who have succeeded in this course;
1) 1. Students will be able to critically review and synthesize academic literature in Data Sceience. 2) 2. Students will demonstrate an understanding of complex concepts and trends in Data Sceience. 3) 3. Students will design and propose original research that contributes to the field. 4) 4. Students will enhance their oral and written communication skills within a professional and academic context. 5) 5. Students will apply theoretical concepts to real-world business scenarios through case study analysis. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | 1. Introduction to Seminar and Overview of DS Research Trends | |
| 2) | Critical Analysis Techniques for Scholarly Articles and Research | |
| 3) | Detailed Review of Current DS Journal Articles – Part 1 | |
| 4) | Detailed Review of Current DS Journal Articles – Part 2 | |
| 5) | Case Study Analysis: Implementation of Information Systems | |
| 6) | Technology Adoption and Diffusion in Organizations | |
| 7) | Presentation Skills Workshop for DS Research | |
| 8) | Presentation Skills Workshop for DS Research | |
| 9) | Guest Speaker Session: Current Issues in DS | |
| 10) | Evaluation of DS Case Studies – Emerging Technologies | |
| 11) | Student Presentations of Original Research Proposals – Part 1 | |
| 12) | Student Presentations of Original Research Proposals – Part 2 | |
| 13) | Workshop on Academic Writing for DS | |
| 14) | Ethics in DS Research and Implications for Management | |
| 15) | Preparation for Final Presentations of Research Findings | |
| 16) | Preparation for Final Presentations of Research Findings |
Sources
| Course Notes / Textbooks: | "Harvard Business Review" for case studies and discussions on the intersection of technology and business. |
| References: | "Harvard Business Review" for case studies and discussions on the intersection of technology and business. |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
|---|---|---|---|---|---|
| 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 |
Course - Learning Outcome Relationship
| 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 |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Presentation | 1 | % 100 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 100 | |
| PERCENTAGE OF FINAL WORK | % | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Workload |
| Course Hours | 14 | 42 |
| Presentations / Seminar | 15 | 180 |
| Total Workload | 222 | |