MATHEMATICS (TURKISH, PHD) | |||||
PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
CYS5172 | Advanced Computer Forensics | Fall | 3 | 0 | 3 | 12 |
The course opens with the approval of the Department at the beginning of each semester |
Language of instruction: | En |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi AHMET NACİ ÜNAL |
Course Objectives: | To teach advanced level computer forensic techniques. |
The students who have succeeded in this course; Effective use of artificial intelligence in the areas of forensics, in this context, ensure research in the field of artificial intelligence. |
Natural and Artificial Intelligence. Intuitive Problem Resolution. Information Modeling and Predicate Logic. Logic Programming. Applicability of Expert Systems and Forensic Computing. Applicability of Artificial Neural Networks and Forensic Computing. Applicability of Genetic Algorithms and Forensic Computing. Applicability of Fuzzy Logic and Forensic Computing. Applicability of Natural Language Processing and Forensic Computing. Applicability of Audio Processing and Forensic Computing. Applicability of Image Processing and Forensic Computing. Biometry Artificial Intelligence Applications I (Face Detection). Biometry Artificial Intelligence Applications II Fingerprint). Biometry Artificial Intelligence Applications III Character Recognition, Handwriting). |
Week | Subject | Related Preparation | |
1) | Natural and Artificial Intelligence | Lecturer notes | |
2) | Intuitive Problem Resolution | Lecturer notes | |
3) | Information Modeling and Predicate Logic | Lecturer notes | |
4) | Logic Programming | Lecturer notes | |
5) | Applicability of Expert Systems and Forensic Computing | Lecturer notes | |
6) | Applicability of Artificial Neural Networks and Forensic Computing | Lecturer notes | |
7) | Applicability of Genetic Algorithms and Forensic Computing | Lecturer notes | |
8) | Applicability of Fuzzy Logic and Forensic Computing | Lecturer notes | |
9) | Applicability of Natural Language Processing and Forensic Computing | Lecturer notes | |
10) | Applicability of Audio Processing and Forensic Computing | Lecturer notes | |
11) | Applicability of Image Processing and Forensic Computing | Lecturer notes | |
12) | Biometry Artificial Intelligence Applications I (Face Detection) | Lecturer notes | |
13) | Biometry Artificial Intelligence Applications II Fingerprint) | Lecturer notes | |
14) | Biometry Artificial Intelligence Applications III Character Recognition, Handwriting) | Lecturer notes |
Course Notes: | Network Forensics, Ric Messier. 2017. Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation. Lee Reiber, 2016. |
References: | Ders notları |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 10 | % 0 |
Laboratory | 0 | % 0 |
Application | 0 | % 0 |
Field Work | 0 | % 0 |
Special Course Internship (Work Placement) | 0 | % 0 |
Quizzes | 0 | % 0 |
Homework Assignments | 4 | % 10 |
Presentation | 1 | % 10 |
Project | 0 | % 0 |
Seminar | 0 | % 0 |
Midterms | 1 | % 20 |
Preliminary Jury | 0 | % 0 |
Final | 1 | % 60 |
Paper Submission | 0 | % 0 |
Jury | 0 | % 0 |
Bütünleme | % 0 | |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 40 | |
PERCENTAGE OF FINAL WORK | % 60 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 0 | 0 | 0 |
Special Course Internship (Work Placement) | 0 | 0 | 0 |
Field Work | 0 | 0 | 0 |
Study Hours Out of Class | 14 | 12 | 168 |
Presentations / Seminar | 2 | 3 | 6 |
Project | 0 | 0 | 0 |
Homework Assignments | 4 | 8 | 32 |
Quizzes | 0 | 0 | 0 |
Preliminary Jury | 0 | 0 | 0 |
Midterms | 1 | 20 | 20 |
Paper Submission | 0 | 0 | 0 |
Jury | 0 | 0 | 0 |
Final | 1 | 20 | 20 |
Total Workload | 288 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |