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: | DATS5102 | ||||
| Course Name: | Regulations in the Field of Data: PDPA, GDPR, FERPA, HIPPA | ||||
| Semester: | Spring | ||||
| Course Credits: |
|
||||
| Language of instruction: | English | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Compulsory Courses | ||||
| Course Level: |
|
||||
| Mode of Delivery: | Face to face | ||||
| Course Coordinator: | Doç. Dr. ŞEBNEM ÖZDEMİR | ||||
| Course Lecturer(s): |
Prof. Dr. BATUHAN KOCAOĞLU |
||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | This course aims to provide students with an in-depth understanding of the major data protection regulations affecting the field of data science. It will cover key aspects of lawful data handling practices, compliance, and the implications of these regulations on organizations. The course will interpret the legal jargon into practical knowledge that can be applied across various industries, ensuring students are well-versed with the skills required to navigate the complex landscape of data protection laws and help their organizations manage data responsibly. |
| Course Content: | 1. Introduction to Data Regulation: PDPA, GDPR, FERPA, HIPAA 2. Understanding the General Data Protection Regulation (GDPR) Framework 3. Exploring the Personal Data Protection Act (PDPA) and its implications 4. The role of the Family Educational Rights and Privacy Act (FERPA) in protecting educational information 5. Health Insurance Portability and Accountability Act (HIPAA) Privacy, Security, and Breach Notification Rules |
Learning Outcomes
|
The students who have succeeded in this course;
1) Grasp the core principles and requirements of GDPR, PDPA, FERPA, and HIPAA. 2) Analyze case studies to understand enforcement and compliance issues surrounding the regulations. 3) Develop a compliance plan to meet the requirements of these regulations within an organization. 4) Identify the rights of data subjects and the obligations of data processors and controllers. 5) Effectively communicate the impact and significance of data regulations to a non-specialized audience. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Overview of Data Protection and Privacy Laws | |
| 2) | Detailed Analysis of the GDPR: Scope and Key Concepts | |
| 3) | Rights of Data Subjects and GDPR Compliance Obligations | |
| 4) | PDPA's Role in Data Protection: Comparison with GDPR | |
| 5) | Application of PDPA in Various Jurisdictions and its Global Impact | |
| 6) | Exploring FERPA and Its Influence on Educational Institutions | |
| 7) | Understanding HIPAA and Its Importance in Healthcare Data | |
| 8) | midterm exam | |
| 9) | Case Studies: GDPR Enforcement and Compliance Issues | |
| 10) | Case Studies: PDPA in Practice Across Different Nations | |
| 11) | FERPA's Real-world Applications and Limitations | |
| 12) | Case Studies: HIPAA Violations and Legal Proceedings | |
| 13) | Integrating Data Regulations into Business Processes | |
| 14) | Creating and Managing a Data Regulation Compliance Program | |
| 15) | Future Directions and Emerging Trends in Data Protection Laws | |
| 16) | Final Exam |
Sources
| Course Notes / Textbooks: | Herhangi bir ders kitabı bulunmamaktadır. There is no textbook. |
| References: | Güncel makaleler, kitaplar kullanılacaktır. Current articles and books will be used. |
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 | 2 |
| 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 |
| Midterms | 1 | % 40 |
| Final | 1 | % 60 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
| Midterms | 1 | 60 | 1 | 61 | |||
| Final | 1 | 80 | 1 | 81 | |||
| Total Workload | 142 | ||||||