Türkçe
Graduate School Of Natural And Applied Sciences Master of Science Programme in Computer Engineering

Qualification Awarded

Master of Science

Specific Admission Requirements

The language proficiency and other exam requirements along with the number of candidates for admission to the program are announced each semester. Applications are evaluated in accordance with the Muğla Sıtkı Koçman University Postgraduate Education-Teaching and Examination Regulation.

Qualification Requirements

Students must be successful in seminar presentations and thesis defenses.

Recognition of Prior Learning

Students from other programs can be accepted in quotas and according to conditions determined at the beginning of the academic term. Applications for program transfer are evaluated according to Muğla Sıtkı Koçman University Program Transfer Regulation.

History

The program accepted its first student in 2023.

Profile of the Programme

The program accepts students twice a year, in the fall and spring semesters. Students can benefit from exchange programs such as ERASMUS.Students are encouraged to work part-time in the industry.

Program Outcomes

1- Uses basic theoretical and applied knowledge related to general engineering in the fields of mathematics and science in solving complex engineering problems.
2- Identifies, defines, models and solves complex problems in computer science and informatics.
3- Selects and applies appropriate analysis, modeling and solution methods for problems in computer science and informatics.
4- Designs experimental environments, collects and organizes necessary data, performs experiments and analyzes the findings in order to obtain solutions to complex problems in computer science and informatics and to improve existing solutions.
5- Designs complex systems, subsystems, components and processes that will meet a certain need in computer-based systems by applying modern design methods under realistic constraints and conditions and carries out all stages of the life cycle of the resulting application.
6- Is aware of the possible effects of information applications in individual, institutional, social and universal dimensions in areas such as economic, environmental, social, political, ethical, health, security, individual freedoms, manufacturability and sustainability. Takes these effects and their legal aspects into consideration as constraints in the complex systems and processes he designs.
7- Gains knowledge on topics such as project management, risk management, change management, standards used in engineering applications, innovation, entrepreneurship and sustainable development.
8- Uses the skills acquired on interdisciplinary problems. Works effectively individually, in interdisciplinary and multidisciplinary teams.
9- Perceives and embraces professional and ethical responsibility.
10- Has awareness of the necessity of lifelong learning and the ability to achieve it.

Exam Regulations & Assesment & Grading

The course evaluations in this program, depending on the course, are based on the midterm exams, final exams, applications done within the scope of the course, homework, projects, presentations and thesis work.

Graduation Requirements

Students must complete at least seven courses, special studies courses, a seminar course, a thesis proposal, and a thesis study. The minimum graduation credit of the program is 120 ECTS.

Occupational Profiles of Graduates

Graduates of the program are employed in the IT sector, which is developing and has an increasing need for human resources.

Access to Further Studies

Program graduates can apply national or international PhD programs.

Mode of Study

Formal Education

Programme Director

ECTS Coordinator

Asist Prof.Dr. Barış İŞÇİ PEMBECİ

Course Structure Diagram with Credits

1. Year - 1. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
CENG5501 Big Data Systems Elective 3 0 6
CENG5503 Deep Learning Elective 3 0 6
CENG5505 Advanced Database Systems Elective 3 0 6
CENG5507 Statistical Data Analysis Elective 3 0 4
CENG5509 Parallel Programming Techniques Elective 3 0 6
CENG5511 Data and Information Visualization Elective 3 0 6
CENG5513 Advanced Computer Vision Elective 3 0 6
CENG5515 Algorithm Design and Analysis Elective 3 0 6
CENG5517 Communication Networks Elective 3 0 6
CENG5519 Advanced Unix Elective 3 0 6
CENG5521 Artificial Intelligence Applications in Medicine Elective 3 0 6
CENG5523 Biomedical Informatics Elective 3 0 6
CENG5525 Machine Learning for Streaming Data Elective 3 0 6
CENG5721 Special Studies Required 4 0 6
FBE5061 Effective Scientific Presentation Techniques Elective 3 0 6
FBE5080 Research Methods and Scientific Ethics Required 2 0 2
       
1. Year - 2. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
CENG5502 Advanced Algorithms Elective 3 0 6
CENG5504 Security Engineering Elective 3 0 6
CENG5506 Advanced Natural Language Processing Elective 3 0 6
CENG5508 Concepts of Object-Oriented Programming Elective 3 0 6
CENG5510 R Programming for Data Science Elective 3 0 6
CENG5512 Special Topics in Computational Linguistics and Intelligent Text Processing Elective 3 0 6
CENG5514 Bioinformatics Algorithms Elective 3 0 6
CENG5516 Category Theory in Computer Science Elective 3 0 6
CENG5518 Program Verification Elective 3 0 6
CENG5520 Interactive Theorem Proving Elective 3 0 6
CENG5522 Secure Software Design and Programming Elective 3 0 6
CENG5722 Special Studies Required 4 0 6
CENG5790 Seminar Required 0 2 6
FBE5550 Project Development and Management Elective 3 0 6
       
2. Year - 1. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
CENG5723 Special Studies Required 4 0 6
       
2. Year - 2. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
CENG5724 Special Studies Required 4 0 6
CENG5802 M.Sc. Thesis Required 0 0 24
       
 

Evaluation Questionnaires

Course & Program Outcomes Matrix

1. Year - 1. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10
Big Data Systems5555555555
Deep Learning5555555555
Advanced Database Systems5555555555
Statistical Data Analysis          
Parallel Programming Techniques 5555555555
Data and Information Visualization5555555555
Advanced Computer Vision5555555555
Algorithm Design and Analysis5555555555
Communication Networks          
Advanced Unix5555555555
Artificial Intelligence Applications in Medicine5555555555
Biomedical Informatics5555555555
Machine Learning for Streaming Data5555555555
Special Studies5555555555
Effective Scientific Presentation Techniques          
Research Methods and Scientific Ethics          
           
1. Year - 2. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10
Advanced Algorithms5555555555
Security Engineering5555555555
Advanced Natural Language Processing5555555555
Concepts of Object-Oriented Programming5555555555
R Programming for Data Science5555555555
Special Topics in Computational Linguistics and Intelligent Text Processing5555555555
Bioinformatics Algorithms5555555555
Category Theory in Computer Science5555555555
Program Verification5555555555
Interactive Theorem Proving5555555555
Secure Software Design and Programming          
Special Studies5555555555
Seminar5555555555
Project Development and Management          
           
2. Year - 1. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10
Special Studies555555 555
           
2. Year - 2. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10
Special Studies5555555555
M.Sc. Thesis5555555555
           
 

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