DEGREE PROGRAMMES

: Computer Science

General Description

History

Department of Computer Science started offering undergraduate program in 2012-2013 academic year and the language of instruction is Turkish and only formal education program is provided. Besides the professional knowledge in Soft Computing, Data Mining, Intelligent Systems, Fuzzy Logic and Optimization, the degree program in the Deparment of Computer Science also provides its graduates knowledge in Statistics, Computer Engineering and Mathematics.

Qualification Awarded

Computer Science

Level of Qualification

First Cycle (Bachelor's Degree)

Specific Admission Requirements

High school diploma, placement through a nation-wide Student Selection Examination.

Specific Arrangements for Recognition of Prior Learning (Formal, Non-Formal and Informal)

For students who intend to transfer to Dokuz Eylül University from universities in Türkiye and in foreign countries, the articles of Regulation on the principles of student transfer between programs at associate and undergraduate degrees in higher education institutions, double major and minor program standards and principles on credit transfers between institutions as well as the Evaluation Criteria on Student Transfer determined by Dokuz Eylül University Senate are implemented.
The vertical transfers of the graduates of Vocational Schools to undergraduate programs related to their completed programs are subject to the rules of Regulation on the continuation of the graduates of Vocational Schools and Distant Learning Programs to undergraduate programs.

Qualification Requirements and Regulations

To graduate from this 4 year program, students are required to successfully complete all courses and satisfy a minimum of 240 ECTS credits. The students also need to complete the 32 weekdays practical training program, complete the graduation project and have a cumulative grade point average of a minimum of 2.00 / 4.00.

Profile of the Programme

Recently, concepts such as Soft Computing, Data Mining, Intelligent Systems, Fuzzy Logic, Fuzzy Sets, and Management Support Systems have begun to be used successfully in Medicine, Economics, Social and so on areas. The aim of the program is to train graduates who would investigate and develop the above-mentioned current scientific technologies and use them in practice. Almost every enterprise and scientific organization accumulate a large extents of data in their computing environment. Graduates of this program are expected to generate new information by analyzing and evaluating this data. On top of professional expertise, the alumni will gain knowledge in areas such as Statistics, Computer Engineering and Mathematics as well.
In addition to professional educational activities, the department is also actively involved in applied and theoretical research. Successful students of the program may also complete Minor Program in Department of Statistics and Mathematics. Students who successfully complete the Minor Program receive a certificate in the second program. In addition, students who successfully carry out the undergraduate program of our department, they can also do in Biology, Physics, Statistics, Chemistry and Mathematics in accordance with the Regulation on the Principles of Transfer between Associate and Undergraduate Degree Programs in Higher Education Institutions, Double Major, Minor and Inter-Institutional Credit Transfer.
The Bologna Process (European Higher Education Area compliance studies) is underway in the department that will allow citizens of countries from European Higher Education Area to have easier access to get higher education and to work within Europe. During the Bologna compliance studies conducted in the department, the aims and outcomes of the Computer Science program that was set are updated in parallel to the focus group interview and the European Education Area principles. Diploma supplements are provided to graduates since 2012. The university received the Diploma Supplement Label in 2012.
The department has an understanding that supports the exchange of students and academics by making bilateral agreements with quality institutions with international reputation, and that they learn from talented, acquired knowledge and experiences.

Key Learning Outcomes

1   Having technical information about basic concepts, terminology and theoretical and applied methods fundamentally in computer science topics,
2   Be able to follow essential developments in the area, to construct mathematical models and to have ability to comment on data, be able to define problems, produce solutions and realize the solutions by means of programming languages,
3   Have ability to work individually and participate in any multidisciplinary team effectively, have self confidence in taking on responsibility,
4   Have ability to use the time efficiently in producing solution process by analytic thinking ability,
5   Be able to follow up-to-date technical literature and evaluate the acquired information with critical approach, have ability to use databases and other data resources,
6   Have the awareness of necessity in lifetime learning; have ability to follow the progress in science and technology and renovate himself consistently,
7   Be able to inform related individuals or organizations about the subjects in computer science; be able to transmit ideas and solution suggestions about the problems in written or orally,
8   Arrange and realize projects and events for social environment in which he lives by means of social responsibility awareness,
9   Be able to follow information about the field by using English as a foreign language and be able to communicate with his colleagues,
10   Be able to integrate discoveries and outcomes in field of computer science with other disciplines,
11   Have ability to share conceptual and technical information with experts in computer science in detail and with non-experts basically,
12   Have social, scientific and ethical values in processing, storing and interpreting data,
13   Become master in algorithmic solution methods and programming language.

Occupational Profiles of Graduates with Examples

Graduates of this program can be employed to the departments of Data Analysis, Data Processing, Software Development, Project Development, Research & Development and similar departments of public and private sector.

Access to Further Studies

Students who graduate from this program can apply for second cycle programs.

Course Structure Diagram with Credits

The course structure and associated credits are provided in the Educational Plan given in the appendix.
T: Theoretical P: Practice L: Laboratory
B: Spring Semester G: Fall Semester H: Full Year
1 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 ATA 1001 PRINCIPLES OF ATATURK AND HISTORY OF THE TURKISH REVOLUTION I REQUIRED 2 0 0 2
G 2 BÄ°L 1005 DISCRETE MATHEMATICS AND LOGIC REQUIRED 4 0 0 6
G 3 BÄ°L 1007 INFORMATION TECHNOLOGIES AND APPLICATIONS REQUIRED 2 2 0 4
G 4 BÄ°L 1011 INTRODUCTION TO COMPUTER SCIENCE I REQUIRED 2 2 0 6
G 5 BÄ°L 1013 TECHNICAL ENGLISH I REQUIRED 2 0 0 2
G 6 FSH 0001 COMMUNICATION SKILLS REQUIRED 2 0 0 2
G 7 FSH 0002 PROFESSIONAL VALUES AND ETHICS REQUIRED 2 0 0 2
G 8 KPD 1000 CAREER PLANNING REQUIRED 1 0 0 2
G 9 MAT 1009 CALCULUS I REQUIRED 4 0 0 6
G 10 YDÄ° 1007 FOREIGN LANGUAGE I (ENGLISH) REQUIRED 2 0 0 2
G 0 - ELECTIVE COURSE ELECTIVE - - - -4
TOTAL:   30
 
2. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 ATA 1002 PRINCIPLES OF ATATURK AND HISTORY OF THE TURKISH REVOLUTION II REQUIRED 2 0 0 2
B 2 BÄ°L 1004 TECHNICAL ENGLISH II. REQUIRED 2 0 0 3
B 3 BÄ°L 1006 LINEAR ALGEBRA AND ANALYTIC GEOMETRY REQUIRED 4 0 0 6
B 4 BÄ°L 1012 INTRODUCTION TO COMPUTER SCIENCE II REQUIRED 2 2 0 7
B 5 BÄ°L 1014 INTRODUCTION TO STATISTICS REQUIRED 3 0 0 4
B 6 MAT 1010 CALCULUS II REQUIRED 4 0 0 6
B 7 YDÄ° 1006 FOREIGN LANGUAGE II (ENGLISH) REQUIRED 2 0 0 2
B 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
2 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BDE 1003 PHYSICAL EDUCATION ELECTIVE 2 0 0 2
B 2 GSH 1003 FOLK DANCING ELECTIVE 2 0 0 2
B 3 GSM 1003 MUSIC ELECTIVE 2 0 0 2
B 4 GSR 1003 PAINTING ELECTIVE 2 0 0 2
 
3 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 2009 GRAPHY THEORY REQUIRED 4 0 0 6
G 2 BÄ°L 2011 ALGORITHMS AND DATA STRUCTURES REQUIRED 2 2 0 6
G 3 BÄ°L 2013 NUMERICAL ANALYSIS REQUIRED 2 2 0 6
G 4 BÄ°L 2015 OBJECT ORIENTED ANALYSIS AND DESIGN REQUIRED 2 2 0 5
G 5 BÄ°L 2017 DIGITAL DESIGN REQUIRED 3 0 0 5
G 6 TDL 1001 TURKISH LANGUAGE I REQUIRED 2 0 0 2
G 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
4. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BÄ°L 2004 DATABASE MANAGEMENT REQUIRED 2 2 0 5
B 2 BÄ°L 2008 OPERATING SYSTEMS REQUIRED 3 0 0 4
B 3 BÄ°L 2012 OBJECT ORIENTED PROGRAMMING REQUIRED 2 2 0 7
B 4 BÄ°L 2014 MULTIVARIATE DATA ANALYSIS REQUIRED 3 0 0 5
B 5 BÄ°L 2016 MATHEMATICAL PROGRAMMING REQUIRED 2 2 0 7
B 6 TDL 1002 TURKISH LANGUAGE II REQUIRED 2 0 0 2
B 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
5 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 3009 FUZZY LOGIC AND FUZZY SETS REQUIRED 3 0 0 6
G 2 BÄ°L 3013 INTRODUCTION TO DATA MINING REQUIRED 2 2 0 6
G 3 BÄ°L 3015 THE DESIGN AND ANALYSIS OF ALGORITHMS REQUIRED 2 2 0 6
G 0 - ELECTIVE COURSE ELECTIVE - - - 12
TOTAL:   30
 
5 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 3101 COMPUTER GRAPHICS ELECTIVE 3 0 0 5
G 2 BÄ°L 3103 DIGITAL SIGNAL PROCESSING ELECTIVE 3 0 0 5
G 3 BÄ°L 3111 SOFTWARE PROJECT MANAGEMENT ELECTIVE 3 0 0 5
G 4 BÄ°L 3113 VISUAL PROGRAMMING LANGUAES ELECTIVE 2 2 0 5
G 5 BÄ°L 3121 GEOGRAPHIC INFORMATION SYSTEMS (GIS) ELECTIVE 2 2 0 5
G 6 BÄ°L 3123 DECISION SUPPORT SYSTEMS ELECTIVE 2 2 0 5
G 7 BÄ°L 3125 OPERATIONS RESEARCH ELECTIVE 2 2 0 5
G 8 BÄ°L 3127 MOBILE PROGRAMMING I ELECTIVE 2 2 0 5
G 9 BÄ°L 3129 CONCEPTS OF PROGRAMMING LANGUAGES ELECTIVE 3 0 0 5
G 10 FÄ°Z 3117 PHYSICS FOR COMPUTER SCIENCE I ELECTIVE 3 0 0 5
 
6. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BÄ°L 3006 COMBINATORIAL OPTIMIZATION REQUIRED 4 0 0 7
B 2 BÄ°L 3010 COMPUTER ORGANIZATION REQUIRED 3 0 0 7
B 3 BÄ°L 3012 COMPUTER NETWORKS REQUIRED 3 0 0 6
B 0 - ELECTIVE COURSE ELECTIVE - - - 10
TOTAL:   30
 
6 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BÄ°L 3102 INTRODUCTION TO TEXT AND WEB MINING ELECTIVE 3 0 0 5
B 2 BÄ°L 3104 DIGITAL IMAGE PROCESSING ELECTIVE 3 0 0 5
B 3 BÄ°L 3108 TIME SERIES MINING ELECTIVE 3 0 0 5
B 4 BÄ°L 3110 SCIENTIFIC COMPUTING ELECTIVE 3 0 0 5
B 5 BÄ°L 3112 MACHINE LEARNING ELECTIVE 3 0 0 5
B 6 BÄ°L 3114 SOFTWARE ENGINEERING PRINCIPLES ELECTIVE 3 0 0 5
B 7 BÄ°L 3122 CONSTRAINT PROGRAMMING ELECTIVE 3 0 0 5
B 8 BÄ°L 3124 GAME THEORY ELECTIVE 3 0 0 5
B 9 BÄ°L 3126 COMPUTER ALGEBRA ELECTIVE 3 0 0 5
B 10 BÄ°L 3130 FUZZY DECISION SYSTEMS ELECTIVE 2 2 0 5
B 11 FÄ°Z 3118 PHYSICS FOR COMPUTER SCIENCE II ELECTIVE 3 0 0 5
 
7 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 4009 GRADUATION PROJECT SENIOR PROJECT 2 0 0 8
G 2 BÄ°L 4091 INTERNSHIP SUMMER TRAINING 0 0 0 8
G 0 - ELECTIVE COURSE ELECTIVE - - - 14
TOTAL:   30
 
7 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 4103 BIOINFORMATICS ELECTIVE 3 0 0 5
G 2 BÄ°L 4105 SYSTEM ANALYSIS ELECTIVE 3 0 0 5
G 3 BÄ°L 4107 COMPUTER GAMES ELECTIVE 3 0 0 5
G 4 BÄ°L 4111 SOFTWARE DESIGN ELECTIVE 3 0 0 5
G 5 BÄ°L 4115 SOFTWARE TESTING AND VERIFICATION ELECTIVE 3 0 0 5
G 6 BÄ°L 4117 BASICS OF INTERNET OF THINGS ELECTIVE 3 0 0 5
G 7 BÄ°L 4119 WEB PROGRAMMING ELECTIVE 2 2 0 5
G 8 BÄ°L 4121 SIMULATION TECHNIQUES ELECTIVE 2 2 0 5
G 9 BÄ°L 4123 SOFT COMPUTING TECHNIQUES ELECTIVE 2 2 0 5
G 10 BÄ°L 4125 SOFTWARE DEBUGGING ELECTIVE 2 2 0 5
G 11 BÄ°L 4127 PARALLEL COMPUTING ELECTIVE 2 2 0 5
G 12 Ä°ST 4203 STATISTICAL METHODS ELECTIVE 3 0 0 5
 
8. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 0 - ELECTIVE COURSE ELECTIVE - - - 30
TOTAL:   30
 
8 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BÄ°L 4102 DISTRIBUTED ALGORITHMS ELECTIVE 3 0 0 5
B 2 BÄ°L 4104 EXPERT SYSTEMS ELECTIVE 3 0 0 5
B 3 BÄ°L 4106 DATA SECURITY ELECTIVE 3 0 0 5
B 4 BÄ°L 4108 PHYSICS ELECTIVE 3 0 0 5
B 5 BÄ°L 4112 ARTIFICIAL INTELLIGENCE ELECTIVE 3 0 0 5
B 6 BÄ°L 4114 INTRODUCTION TO COMPUTATION THEORY ELECTIVE 3 0 0 5
B 7 BÄ°L 4120 EMBEDDED SYSTEM PROGRAMMING ELECTIVE 2 2 0 5
B 8 BÄ°L 4122 INTEGER PROGRAMMING ELECTIVE 2 2 0 5
B 9 BÄ°L 4124 MOBILE PROGRAMMING II ELECTIVE 2 2 0 5
B 10 BÄ°L 4126 SERVICE ORIENTED PROGRAMMING ELECTIVE 2 2 0 5
B 11 Ä°ST 4202 ACTUARY AND RISK MANAGEMENT ELECTIVE 3 0 0 5
 
 
FLEXIBLE ELECTIVE COURSE ACCORDING TO ECTS
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
H 1 GÇD 1000 VOLUNTEERISM STUDIES FACULTY ELECTIVE COURSE 1 2 0 4
H 1 FRM 0001 INTRODUCTION TO EDUCATION 3 0 0 4
H 2 FRM 0002 PRINCIPLES AND METHODS OF LEARNING 3 0 0 4
H 3 FRM 0003 CLASSROOM MANAGEMENT 2 0 0 3
H 4 FRM 0004 SPECIAL TEACHING METHODS 3 0 0 4
H 5 FRM 0005 GUIDANCE AND SPECIAL EDUCATION 3 0 0 4
H 6 FRM 0006 MEASUREMENT AND EVALUATION IN EDUCATION 3 0 0 4
H 7 FRM 0007 EDUCATIONAL PSYCHOLOGY 3 0 0 4
H 8 FRM 0008 INSTRUCTIONAL TECHNOLOGIES 2 0 0 3
H 9 FRM 0009 PRACTICE IN TEACHING 1 8 0 10
H 10 MTH 0001 BLOCKCHAIN TECHNOLOGY AND ITS APPLICATIONS FACULTY ELECTIVE COURSE 2 0 0 2
H 11 MTH 0002 INSTRUMENTAL ANALYSIS-CHROMATOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 12 MTH 0003 HYDROGEN FUEL CELL TECHNOLOGY FACULTY ELECTIVE COURSE 2 0 0 2
H 13 MTH 0004 MEDICAL POLYMERS FACULTY ELECTIVE COURSE 3 0 0 3
H 14 MTH 0005 PRODUCING OPEN SOFTWARE FACULTY ELECTIVE COURSE 2 0 0 2
H 15 MTH 0006 INTRODUCTION TO STATISTICS AND DATA SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 16 MTH 0007 BIG DATA TECHNOLOGIES FACULTY ELECTIVE COURSE 2 0 0 2
H 17 MTH 0008 MEDICAL METROLOGY AND ULTRASONIC APPLICATIONS FACULTY ELECTIVE COURSE 2 0 0 2
H 1 ERA 0001 SOFT COMPUTING TECHNIQUES ERASMUS 2 2 0 5
H 2 ERA 0002 SOFTWARE PROJECT MANAGEMENT ERASMUS 3 0 0 5
H 3 ERA 0003 BIOLOGICAL IMPACTS OF CLIMATE CHANGE ERASMUS 3 0 0 6
H 4 ERA 0004 HUMAN ANATOMY AND PHYSIOLOGY ERASMUS 2 0 0 6
H 5 ERA 0005 QUANTUM PHYSICS FOR EVERYONE ERASMUS 2 2 0 7
H 6 ERA 0006 DARK MATTER AND MYSTERIOUS OF THE UNIVERSE-I ERASMUS 2 2 0 7
H 7 ERA 0007 TIME SERIES MODELS ERASMUS 4 0 0 6
H 8 ERA 0008 ESTIMATION AND HYPOTHESIS TESTING ERASMUS 4 0 0 6
H 9 ERA 0009 DISCRETE MATHEMATICS AND ITS APPLICATIONS ERASMUS 3 0 0 5
H 10 ERA 0010 PROOF TECHNIQUES ERASMUS 2 0 0 2
H 11 ERA 0011 UNDERSTANDING LIFE WITH CODES AND THEIR READINGS ERASMUS 3 0 0 5
H 12 ERA 0012 MATERIAL CHEMISTRY ERASMUS 3 0 0 6
H 13 ERA 0013 NANOMATERIALS AND MEDICAL APPLICATIONS ERASMUS 3 0 0 6
H 14 ERA 0014 HISTORY OF MATHEMATICAL THOUGHT ERASMUS 2 0 0 2
H 15 ERA 0015 INTRODUCTION TO MOBILE PROGRAMMING ERASMUS 2 2 0 5
H 16 FSH 0002 PROFESSIONAL VALUES AND ETHICS FACULTY ELECTIVE COURSE 2 0 0 2
H 17 FSH 0004 PHILOSOPHY OF SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 18 FSH 0006 HISTORY OF SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 19 FSH 0007 SOLUTION OF INTERPERSONAL CONFLICTS FACULTY ELECTIVE COURSE 2 0 0 2
H 20 FSH 0008 SCIENCE IN DAILY LIFE FACULTY ELECTIVE COURSE 2 0 0 2
H 21 FSH 0011 CREATIVITY, RD, Ä°NNOVATION FACULTY ELECTIVE COURSE 2 0 0 2
H 22 FSH 0012 FUTURE PLANNING AND STRATEGY FACULTY ELECTIVE COURSE 2 0 0 2
H 23 FSH 0013 YOUTH ENTREPRENEURSHIP FACULTY ELECTIVE COURSE 2 0 0 2
H 24 FSH 0015 GLOBALIZATION AND THE NEW WORLD ORDER FACULTY ELECTIVE COURSE 2 0 0 2
H 25 FSH 0020 MANAGEMENT FACULTY ELECTIVE COURSE 2 0 0 2
H 26 FSH 0021 ECONOMICS FACULTY ELECTIVE COURSE 2 0 0 2
H 27 FSH 0022 ACCOUNTING FACULTY ELECTIVE COURSE 2 0 0 2
H 28 FSH 0023 MARKETING FACULTY ELECTIVE COURSE 2 0 0 2
H 29 FSH 0024 BASIC LAW FACULTY ELECTIVE COURSE 2 0 0 2
H 30 FSH 0025 MONEY AND BANKING FACULTY ELECTIVE COURSE 2 0 0 2
H 31 FSH 0026 TOTAL QUALITY AND ACCREDITATION FACULTY ELECTIVE COURSE 2 0 0 2
H 32 FSH 0028 FLOWERING PLANTS, NATURE'S HEALING HANDS FACULTY ELECTIVE COURSE 2 0 0 2
H 33 FSH 0029 BASIC BANKING AND INFORMATION TECHNOLOGIES FACULTY ELECTIVE COURSE 2 0 0 2
H 34 FSH 0031 TRANSLATION FACULTY ELECTIVE COURSE 2 0 0 2
H 35 FSH 0032 TEXT ANALYSIS FACULTY ELECTIVE COURSE 2 0 0 2
H 36 FSH 0033 SEMANTICS FACULTY ELECTIVE COURSE 2 0 0 2
H 37 FSH 0034 TERMINOLOGY AND TERMINOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 38 FSH 0035 FINANCIAL ECONOMICS FACULTY ELECTIVE COURSE 2 0 0 2
H 39 FSH 0036 ECONOMIC GLOBALIZATION FACULTY ELECTIVE COURSE 2 0 0 2
H 40 FSH 0040 CHEMISTRY AND ART FACULTY ELECTIVE COURSE 2 0 0 2
H 41 FSH 0041 QUANTUM ERA FACULTY ELECTIVE COURSE 2 0 0 2
H 42 FSH 0042 BASIC STATISTICS FACULTY ELECTIVE COURSE 2 0 0 2
H 43 FSH 0043 REFLECTIONS ON MODERNLIFE FACULTY ELECTIVE COURSE 2 0 0 2
H 44 FSH 0044 SCIENTIFIC WRITING WITH LATEX FACULTY ELECTIVE COURSE 2 0 0 2
H 45 FSH 0045 INTRODUCTION TO PROGRAMMING WITH PYTHON FACULTY ELECTIVE COURSE 2 0 0 2
H 46 FSH 0046 ZOOGEOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 47 FSH 0047 CREATING REPORTS AND PRESENTATIONS BY OFFICE PROGRAMS FACULTY ELECTIVE COURSE 2 0 0 2
H 48 FSH 0048 EXCEL FOR BUSINESS WORLD FACULTY ELECTIVE COURSE 2 0 0 2
H 49 FSH 0049 BIOLOGICAL IMPACTS OF CLIMATE CHANGE FACULTY ELECTIVE COURSE 2 0 0 2
H 50 FSH 0050 PIONEERS OF SCIENCE FACULTY ELECTIVE COURSE 3 0 0 5
H 51 FSH 0051 HEALTH KNOWLEDGE AND FIRST AID FACULTY ELECTIVE COURSE 2 0 0 4
H 52 FSH 0052 REPTILE AND AMPHIBIAN DIVERSITY OF TüRKIYE FACULTY ELECTIVE COURSE 2 0 0 4
H 53 FSH 0053 PROJECT PROPOSAL PREPARATION FACULTY ELECTIVE COURSE 2 0 0 2
H 54 FSH 0054 DATA PREPROCESSING FACULTY ELECTIVE COURSE 2 0 0 2
H 55 FSH 0055 MEDICAL IMAGING SYSTEMS FACULTY ELECTIVE COURSE 2 0 0 2
H 56 FSH 0056 ENVIRONMENTAL RADIOACTIVITY FACULTY ELECTIVE COURSE 2 0 0 2
H 57 FSH 0057 ARTIFICIAL INTELLIGENCE WITH APPLICATIONS FACULTY ELECTIVE COURSE 0 2 0 2
H 58 Ä°HD 1001 HUMAN RIGHTS FACULTY ELECTIVE COURSE 2 0 0 4
 

Examination Regulations, Assessment and Grading

The relevant articles of Education and Examination Regulation of Dokuz Eylül University and Education and Examination Implementation Principles of the Faculty of Science are applicable for exams and course success grades.
The course evaluation criteria are defined for each course by the instructor(s) of the corresponding course and are given in the Course Description Form found in the information package.

Graduation Requirements

Students are required to successfully pass all courses to graduate from this four year program. This degree is awarded to all students who succeed all courses, successfully complete 32 days of practical training program and the Graduation Project, satisfy minimum 240 ECTS credits and have a minimum 2.00 / 4.00 overall Cumulative Grade Point Average (CGPA).

Mode of Study (Full-Time, Part-Time, E-Learning )

Full-time

Programme Director or Equivalent

Prof. Dr. Murat ErÅŸen BERBERLER
Dokuz Eylül University
Faculty of Science, Department of Computer Science
Phone: +90 (232) 301 9500
E-mail: murat.berberler@deu.edu.tr