Semester: 5
General Foundation
ECTS: 6
Hours per week: 3
Professor: T.B.D.
Teaching style: Face to face
Grading: Written exams (50%), Essays / Projects (50%)
Activity | Workload |
---|---|
Lectures | 26 |
Tutorials | 13 |
Essays / Project | 60 |
Independent study | 51 |
Course total | 150 |
The course covers emerging issues and topics of Security and Privacy in the scientific areas of Data Science and Artificial Intelligence (AI). The aim of the course is to create a framework of theoretical and technical knowledge, by identifying vulnerabilities and associated risks, exploring appropriate security mechanisms and techniques to mitigate attacks and threats, and studying specific aspects related to AI and Data Science that generate security and privacy concerns.
Upon successful completion of this course, the student will be:
Related scientific journals:
Internet sources:
The course covers emerging issues and topics of Security and Privacy in the scientific areas of Data Science and Artificial Intelligence (AI). The aim of the course is to create a framework of theoretical and technical knowledge, by identifying vulnerabilities and associated risks, exploring appropriate security mechanisms and techniques to mitigate attacks and threats, and studying specific aspects related to AI and Data Science that generate security and privacy concerns.
Upon successful completion of this course, the student will be:
Related scientific journals:
Internet sources: