GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
ARTIFICIAL INTELLIGENCE TECHNIQUES IN FORENSIC INFORMATICS/5181311
Course Title: ARTIFICIAL INTELLIGENCE TECHNIQUES IN FORENSIC INFORMATICS
Credits 3 ECTS 8
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Assist.Prof.Dr.Hüseyin ÇAKIR
 -- WEB SITE(S) OF LECTURER(S)
  http://www.websitem.gazi.edu.tr/site/hcakir
 -- EMAIL(S) OF LECTURER(S)
  hcakir@gazi.edu.tr, hcakir2000@gmail.com
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Effective use of artificial intelligence in the areas of forensics, in this context, ensure research in the field of artificial intelligence
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  Natural and Artificial Intelligence
2. Week  Intuitive Problem Resolution
3. Week  Information Modeling and Predicate Logic
4. Week  Logic Programming
5. Week  Applicability of Expert Systems and Forensic Computing
6. Week  Applicability of Artificial Neural Networks and Forensic Computing
7. Week  Applicability of Genetic Algorithms and Forensic Computing
8. Week  Applicability of Fuzzy Logic and Forensic Computing
9. Week  Applicability of Natural Language Processing and Forensic Computing
10. Week  Applicability of Audio Processing and Forensic Computing
11. Week  Applicability of Image Processing and Forensic Computing
12. Week  Biometry Artificial Intelligence Applications I (Face Detection)
13. Week  Biometry Artificial Intelligence Applications II Fingerprint)
14. Week  Biometry Artificial Intelligence Applications III Character Recognition, Handwriting)
15. Week  
16. Week  
 -- RECOMMENDED OR REQUIRED READING
  - Nabiyev, V.V. (2005). Yapay Zeka. Seçkin yayıncılık, Ankara. - Russell, S.J. And Norvig, P., Artificial Intelligence : A Modern Approach, Second Edition, Prentice-Hall, 2003. (AIMA) - Luger, G.F., Artificial Intelligence : Structures and Strategies for Complex Problem-Solving, 4th Edition, Addison-Wesley, 2002.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  Not Applicable
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
40
 Assignment
1
60
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
0
0
 Reading
6
5
30
 Searching in Internet and Library
6
5
30
 Designing and Applying Materials
5
5
25
 Preparing Reports
5
5
25
 Preparing Presentation
5
6
30
 Presentation
1
5
5
 Mid-Term and Studying for Mid-Term
1
4
4
 Final and Studying for Final
1
4
4
 Other
0
 TOTAL WORKLOAD: 
195
 TOTAL WORKLOAD / 25: 
7.8
 ECTS: 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Can use theoretical and practical knowledge at the level of expertise acquired in the field.X
2Can analyse the problems related to the field by using research methods.X
3Can systematically pass on up-to-date advancements in the field of Forensic Computing and his or her own work supported by quantitative and qualitative data to the groups related and/or unrelated to the field, written, verbal and graphically.X
4Can use advanced level of informatics and communication technologies with computer software at the required level in the field of Forensic Computing.X
5Adopts life-long learning principle, is open to innovation, participates actively in the development of himself/herself and the institution.X
6Able to use foreign languages at the level required to monitor the foreign resources about Forensic Computing and to communicate with colleagues (European Language Portfolio Global Scale, Level B2).X
7Can criticise the knowledge and skills at the level of expertise acquired in the field and direct his/her learning in the appropriate way.X
8Operates actively as an individual and among interdisciplinary groups.X
9Conducts resource searching in order to acquire information, uses databases and other information resources, evaluates the validity and actuality of information acquired through different resources.X
10Can control the stages of collection, interpretation, application and dissemination of data related to the field of Forensic Computing with respect to social, scientific, cultural and ethical values and can teach these values.X
11Can develop strategy, politics and application plans related to the field of Forensic Computing and can evaluate the results within perspectives of quality processes.X
12Can use the knowledge, problem solving and/or application skills absorbed in the field of Forensic Computing at an interdisciplinary practice.X
13Determines and defines the problems about the field of Forensic Computing, designs relative solutions, selects and applies the appropriate analytical methods and modeling techniques for the purpose.X
14Follows and applies the innovative approaches about the field.X