6 EC
Semester 2, period 4
5274CDTF6Y
| Owner | Master Forensic Science |
| Coordinator | Jaap van Ginkel |
| Part of | Master Forensic Science, year 1 |
| Links | Visible Learning Trajectories |
The following topics/subjects will be addressed:
Digital Forensics and cybercrime intro
Acquisition, Hashing/integrity
Live forensics/ memory forensics
(Smart)phone forensics
Embedded/Device forensics
Network forensics
Multimedia forensics
Big Data forensics
Activity | Hours | |
Hoorcollege | 26 | |
Presentatie | 8 | |
Werkcollege | 52 | |
Self study | 82 | |
Total | 168 | (6 EC x 28 uur) |
Additional requirements for this course:
Attending all scheduled education activities is strongly advised. By doing so, you actively contribute to a lively learning community and significantly improve your chances of successfully completing the course. The designated mandatory activities play a crucial role in achieving the course objectives and are essential for your overall progress.
Additional requirements for this course:
It is presupposed that all students will be present in class.
| Item and weight | Details |
|
Final grade | |
|
70% Report | Must be ≥ 5.5, Mandatory |
|
30% Presentation | Must be ≥ 5.5, Mandatory |
All components will be graded on a scale of 1-10. In order to pass the course, all components and the final grade have to be sufficient, i.e. at least a five and a half. When a student has not fulfilled this requirement, the examiner will register the mark ‘did not fulfill all requirements’ (NAV) whether or not the averaged grade is sufficient. The components will be weighted as follows:
1. report (70%)
2. presentation (30%)
The students will work in groups on the project.
The final grade will be announced at the latest on 21st of April (= 15 working days after the final course activity). Between the 16th of April and May 27th (= 35 working days after the final course activity) a post-exam discussion or inspection moment will be planned. This will be announced on Canvas and/or via email.
| LO | Tested in component | EQ 1 | EQ 2 | EQ 3 | EQ 4 | EQ 5 | EQ 6 | EQ 7 | EQ 8 | EQ 9 | EQ 10 |
| 1 | 1, 2 | x | |||||||||
| 2 | 1, 2 | x | |||||||||
| 3 | 1, 2 | x | |||||||||
| 4 | 1, 2 | x | |||||||||
| 5 | 1, 2 | x | |||||||||
| 6 | 1, 2 | x |
Table of specification: the relation between the Learning Outcomes (LO) of the course, the assessment components of the course and the Exit Qualifications (EQ) of the Master’s Forensic Science (described in the Introduction in the Course Catalogue)
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
Use of GenAI in MFS
Within the Master Forensic Science, you are allowed to use Generative AI (GenAI) to support your learning process process but according to the policy framework and guidelines as defined by the University of Amsterdam. For example, you can use large language models (LLMs) to help your self-study by generating flashcards or generating explanations of concepts. GenAI should be a support tool to help you reach the course's learning objectives, not a system to which you delegate activities that are meant to promote your learning. The course examiner has final say on which use cases are permissible or not within their course.
You may not use GenAI to create any content you submit for assessment, regardless of whether it's graded numerically or on a pass/fail basis. The only exception is if an assignment description explicitly allows GenAI use. In such cases, permissible use is delineated by the course instructor.
Never share personal information, research data, or course materials with a GenAI system, except for UvA AI Chat. This UvA-hosted system was built with GDPR compliance and data security in mind. If in doubt about sharing information, don't share. You can always check with your course coordinator whether any intended use case is responsible.
Teachers are never allowed to use GenAI to grade your work. They may, however, use it to formulate their feedback. Only tools allowed by UvA should be used in research and education. If there is no UvA license for software, use cannot be mandatory in education. This implies that learning objectives must be achievable without the use of non-licensed tools. UvA AI Chat can be used, if used with due consideration and care.
Use within CDTF