1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. COMPUTER ENGINEERING DEPARTMENT
General Information Prog. Learning Outcomes Teaching & Learning Methods Course Structure Course & Learning Outcomes LO - NQF-HETR Relation LO - FOE (Academic) LO - FOE (Vocational)

1281 Computer Engineering

GENERAL INFORMATION
Computer Engineering programme provides graduate level courses and research opportunities in the areas of software, computer hardware and computer sciences.

Objective
The aim of this department is to equip the students with one of the areas of computer science. Graduates are trained to analyze and solve real world problems through research, observation and analysis.

Admission Requirements
In order to apply to the Computer Engineering Master's programme, candidates must have the undergraduate diploma specified in the application requirements and must have a score of 70 in the Quantitative score type from the Academic Personnel and Graduate Education Entrance Examination (ALES). Students whose application is accepted are subjected to a written / oral exam on the announced date and time. Based on the graduate regulations of Pamukkale University, students who get a passing score as a result of ALES, academic grade point average, written / oral exam grade and foreign language score evaluation, if any, are accepted to the master's programme with thesis. There is no foreign language requirement for admission to Computer Engineering Master's programme with thesis.

Graduation Requirements
In order to graduate from the Master's programme in Computer Engineering; 60 ECTS compulsory, elective and seminar course credits, 60 ECTS Specialisation course and Master's Thesis course credits, a total of 120 ECTS must be successfully completed and the academic average determined by the senate for graduation at the end of the education period must be met.

Career Opportunties
Recognition of previous structured lectures in Turkish Higher Education Institutions, transitions in vertical, horizontal and university are realized within the scope of the "Higher Education Regulations", "REGULATION BETWEEN THE BACHELORS AND GRADUATE DEGREE PROGRAMS, ON HIGHER EDUCATION AND TRANSITION BETWEEN DOUBLE MAJOR DALL, SIDE DALL AND CREDIT TRANSFER STANDARDS

Qualification Awarded
Computer Engineering

Level of Qualification
Second Cycle (Master's Degree)

Recognition of Prior Learning
Recognition of previous structured lectures in Turkish Higher Education Institutions, transitions in vertical, horizontal and university are realized within the scope of the "Higher Education Regulations", "REGULATION BETWEEN THE BACHELORS AND GRADUATE DEGREE PROGRAMS, ON HIGHER EDUCATION AND TRANSITION BETWEEN DOUBLE MAJOR DALL, SIDE DALL AND CREDIT TRANSFER STANDARDS

Qualification Requirements and Regulations
In order to graduate from the Master's programme in Computer Engineering; 60 ECTS compulsory, elective and seminar course credits, 60 ECTS Specialisation course and Master's Thesis course credits, a total of 120 ECTS must be successfully completed and the academic average determined by the senate for graduation at the end of the education period must be met.

Access to Further Studies
May apply to PhD programs

Mode of Study
Full Time

Examination Regulations, Assessment and Grading
Measurement and evaluation methods that is applied for each course, is detailed in "Course Structure&ECTS Credits".

Contact (Programme Director or Equivalent)
PositionName SurnamePhoneFaxE-Mail
HEAD OF THE DEPARTMENT OF INSTITUTEProf. Dr. TUFAN TURACI  tturaci@pau.edu.tr


PROGRAM LEARNING OUTCOMES
1Possession of theoretical and applied knowledge in computer sciences
2Possession of theoretical and applied knowledge in mathematics and basic sciences
3Possession of skills for identifying, analyzing and solving engineering problems
4Possession of skills for designing a system, subsystem or a process to meet specified requirements
5Possession of skills for determining necessary tools and techniques for engineering applications
6Possession of skills for designing experiments, conducting experiments, data collection and analysis
7Possession of skills for working as parts of single and multidisciplinary teams
8Possession of skills for effective oral and written communication
9Possession of skills for continuous learning and self improvement
10Possession of capabilities for ethical conduct
11Possession of capabilities for project and risk management in the work place
12Possession of capabilities for understanding health, environmental and safety aspects and their legal implications
TEACHING & LEARNING METHODS
NameComments
LecturingLecturing is one of the methods that come first, where the teacher is in the center. It is a method where the teacher actively describes topics and the students are passive listeners. With this method, lesson proceeds in the form of report, description and explanation.
DebateDepending on the situation, debate is a tool that allows all students, or a specific portion of the class to participate in the lesson. In this method, members of the group discuss a topic by addressing the various points of view and discuss alternative opinions about problem-solving.
DemonstrationIn this method the teacher demonstrates, an experiment, test, in front of the class. And then assists students to do so too. Students learn not only by just by looking and watching, but also by taking part and participating. This method is usually applied when teaching skills.
Problem SolvingThe name given to any doubt or ambiguity that arises is, a problem. Problems which usually have a role in human life, that have preventing or annoying aspects are solved by considering the stages of scientific methods. (a) Problems are determined. (b) The problem is identified. 
PerformanceIn this method, the teacher performs activities such as experiments and demonstrations in front of the class, students try to learn by looking and watching. This method is usually applied where there are limited facilities and in dealing with dangerous experimental situations.
Questions –AnswersThe different types of Questions used (associative, differential, assessment, requesting information, motivating, and brainstorming) although students get in to more active positions during the process; the method is teacher-centered. If possible Questions, that serve a purpose and

PO - NQF-HETR Relation
NQF-HETR CategoryNQF-HETR Sub-CategoryNQF-HETRLearning Outcomes
INFORMATION  01
INFORMATION  02
SKILLS  01
SKILLS  02
SKILLS  03
COMPETENCIESCommunication and Social Competence 01
COMPETENCIESCommunication and Social Competence 02
COMPETENCIESCommunication and Social Competence 03
COMPETENCIESCommunication and Social Competence 04
COMPETENCIESCompetence to Work Independently and Take Responsibility 01
COMPETENCIESCompetence to Work Independently and Take Responsibility 02
COMPETENCIESCompetence to Work Independently and Take Responsibility 03
COMPETENCIESField Specific Competencies 01
COMPETENCIESField Specific Competencies 02
COMPETENCIESField Specific Competencies 03
COMPETENCIESLearning Competence 01
    

PO - FOE (Academic)
FOE CategoryFOE Sub-CategoryFOELearning Outcomes
INFORMATION  01
INFORMATION  02
INFORMATION  03
INFORMATION  04
SKILLS  01
SKILLS  02
SKILLS  03
SKILLS  04
COMPETENCIESCommunication and Social Competence 01
COMPETENCIESCommunication and Social Competence 02
COMPETENCIESCommunication and Social Competence 03
COMPETENCIESCommunication and Social Competence 04
COMPETENCIESCommunication and Social Competence 05
COMPETENCIESCommunication and Social Competence 06
COMPETENCIESCommunication and Social Competence 07
COMPETENCIESCommunication and Social Competence 08
COMPETENCIESCompetence to Work Independently and Take Responsibility 01
COMPETENCIESCompetence to Work Independently and Take Responsibility 02
COMPETENCIESCompetence to Work Independently and Take Responsibility 03
COMPETENCIESCompetence to Work Independently and Take Responsibility 04
COMPETENCIESCompetence to Work Independently and Take Responsibility 05
COMPETENCIESCompetence to Work Independently and Take Responsibility 06
COMPETENCIESField Specific Competencies 01
COMPETENCIESField Specific Competencies 02
COMPETENCIESField Specific Competencies 03
COMPETENCIESField Specific Competencies 04
COMPETENCIESLearning Competence 01
COMPETENCIESLearning Competence 02
COMPETENCIESLearning Competence 03
COMPETENCIESLearning Competence 04
    

PO - FOE (Vocational)
FOE CategoryFOE Sub-CategoryFOELearning Outcomes
INFORMATION  01
INFORMATION  02
SKILLS  01
SKILLS  02
SKILLS  03
SKILLS  04
COMPETENCIESCommunication and Social Competence 01
COMPETENCIESCommunication and Social Competence 02
COMPETENCIESCommunication and Social Competence 03
COMPETENCIESCommunication and Social Competence 04
COMPETENCIESCommunication and Social Competence 05
COMPETENCIESCompetence to Work Independently and Take Responsibility 01
COMPETENCIESCompetence to Work Independently and Take Responsibility 02
COMPETENCIESCompetence to Work Independently and Take Responsibility 03
COMPETENCIESCompetence to Work Independently and Take Responsibility 04
COMPETENCIESCompetence to Work Independently and Take Responsibility 05
COMPETENCIESField Specific Competencies 01
COMPETENCIESField Specific Competencies 02
COMPETENCIESField Specific Competencies 03
COMPETENCIESField Specific Competencies 04
COMPETENCIESLearning Competence 01
COMPETENCIESLearning Competence 02
COMPETENCIESLearning Competence 03
COMPETENCIESLearning Competence 04
COMPETENCIESLearning Competence 05
    

COURS STRUCTURE & ECTS CREDITS
Year :
Course Plan

1st Semester Course Plan
Course CodeCourse TitleL+P HourECTSCourse Type
CENG 501 ADVANCED PROGRAMMING TECHNIQUES 3+0 7,5 Compulsory
FBE 610 METHODS OF RESEARCH AND ETHICS 3+0 7,5 Compulsory
- Computer Engineering Elective-1 3+0 7,5 Elective
- Computer Engineering Elective-1 3+0 7,5 Elective
  Total 30  
1st Semester Elective Groups : Computer Engineering Elective-1

2nd Semester Course Plan
Course CodeCourse TitleL+P HourECTSCourse Type
CENG 599 SEMINAR 0+2 7,5 Compulsory
CENG 504 ALGORITHM DESIGN AND ANALYSIS 3+0 7,5 Compulsory
- Computer Engineering Elective-2 3+0 7,5 Elective
- Computer Engineering Elective-2 3+0 7,5 Elective
  Total 30  
2nd Semester Elective Groups : Computer Engineering Elective-2

3rd Semester Course Plan
Course CodeCourse TitleL+P HourECTSCourse Type
CENG 700 FIELD OF STUDY COURSE 6+0 10 Compulsory
CENG 500 MASTER'S THESIS 0+0 20 Compulsory
  Total 30  

4th Semester Course Plan
Course CodeCourse TitleL+P HourECTSCourse Type
CENG 500 MASTER'S THESIS 0+0 20 Compulsory
CENG 700 FIELD OF STUDY COURSE 6+0 10 Compulsory
  Total 30  


COURSE & PROGRAM LEARNING OUTCOMES
Year : Compulsory Courses
Course TitleC/EPO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
ADVANCED PROGRAMMING TECHNIQUESC* **   * ** 
ALGORITHM DESIGN AND ANALYSISC**** *****  
FIELD OF STUDY COURSEC***** ***** 
MASTER'S THESISC************
METHODS OF RESEARCH AND ETHICSC            
POSTGRADUATE COUNSELINGC            
SEMINARC************
Click to add elective courses...
Elective Courses
Course TitleC/EPO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
ADVANCED COMPUTER NETWORKSE************
ADVANCED DATABASE MANAGEMENT AND MODELLINGE**** *****  
ADVANCED TECHNIQUES IN COMPUTER SCIENCEE****        
ARTIFICIAL INTELLIGENCE AND ENGINEERING APPLICATIONSE*****       
BIOINFORMATICSE            
COMBINATORIAL OPTIMIZATION AND ALGORITHMSE            
COMPUTATIONAL AND COGNITIVE NEUROSCIENCEE            
COMPUTATIONAL INTELLIGENCE AND ALGORITHMSE            
COMPUTER NETWORKS SECURITYE************
COMPUTER VISIONE            
CONSEPT OF DISTANCE IN GRAPHS AND ALGORITHMSE            
CRYPTOGRAPHIC ALGORITHMS AND SYSTEMSE************
DATA ANALYSIS IN INTERNET OF THINGSE            
DEEP LEARNING AND APPLICATIONSE            
DIGITAL CONTROLE *** *      
DISTRIBUTED SYSTEMSE**** *****  
FUZZY LOGIC AND ENGINEERING APPLICATIONSE*****       
GRAPH THEORY AND ALGORITHMSE**** *    * 
IMAGE PROCESSING AND ENGINEERING APPLICATIONSE*****      *
INFORMATION SYSTEMS AND SYSTEM DESIGNE************
LOGISTICS ENGINEERINGE            
MACHINE LEARNINGE            
MODELLING OF COMMUNICATION NETWORKS AND CONSEPT OF VULNERABILITYE            
NATURAL LANGUAGE PROCESSING WITH APPLICATIONSE            
NEURAL NETWORKS AND ENGINEERING APPLICATIONSE*****       
NEXT GENERATION IOT APPLICATIONSE            
NUMERICAL METHODS IN OPTIMISATIONE**** *    * 
OBJECT-ORIENTED DESIGN AND PROGRAMMING TECHNIQUESE* *** ** ** 
PARALLEL PROGRAMMINGE**** *    * 
PATTERN RECOGNITIONE            
SOFTWARE DEVELOPMENT PROCESSE************
SOFTWARE PROJECT MANAGEMENTE************
L+P: Lecture and Practice
C: Compulsory
E: Elective
PO: Program Learning Outcomes
TH [5]: Too High
H [4]: High
M [3]: Medium
L [2]: Low
TL [1]: Too Low
None [0]: None
FOE [0]: Field of Education
NQF-HETR : National Qualifications Framework For Higher Education in Turkey