Department of Computer Engineering
Chairman’s Welcome Message
Courses

1st Semester

CODE COURSE NAME C/E T P C E
COM106 Introduction to Programming C 3 2 4 6
CHM101 General Chemistry C 3 2 4 5
ENG101 English I C 3 0 2 3
MTH101 Calculus I C 4 0 4 5
PHY101 General Physics I C 3 2 4 5
CAM100 Campus Orientation C 2 0 0 2
YİT101 / TUR101 Turkish for Foreigners I / Turkish Language I C 2 0 2 2
COM001 Computer Engineering Orientation C 2 0 0 2
Total 22 6 20 30

2nd Semester

CODE COURSE NAME C/E T P C E
AII104 Discrete Structures C 3 0 3 5
AII102 Programming & Problem Solving C 3 2 4 6
ENG102 English II C 3 2 2 3
MTH102 Calculus II C 4 0 4 6
PHY102 General Physics II C 3 2 4 6
YİT102 / TUR102 Turkish for Foreigners II / Turkish Language II C 2 0 2 2
GEC351 21st Century Skills E 2 0 0 2
Total 20 4 19 30

3rd Semester

CODE COURSE NAME C/E T P C E
AII001 Logic Design C 3 2 4 6
AII201 Data Structures& Algorithms C 3 2 4 6
AII204 Electrical Circuits C 3 0 3 5
MTH201 Differential Equations C 4 0 4 6
AİT103 / AİT101 Atatürk Principles & Reforms I C 2 0 2 2
MTH113 Linear Algebra C 3 0 3 5
Total 18 4 20 30

4th Semester

CODE COURSE NAME C/E T P C E
AII202 Database Management Systems C 3 2 4 5
AII203 Computer Architecture and Organization C 3 2 4 5
COM208 Electronics I C 3 2 4 5
ENG201 English Communication Skills C 3 0 3 4
AİT104 / AİT102 Atatürk Principles & Reforms II C 2 0 2 2
RE Restricted Electives E 3 0 3 4
COM200 Summer Training I C 0 0 0 5
Total 17 6 20 30

5th Semester

CODE COURSE NAME C/E T P C E
AII302 Operating Systems C 3 0 3 6
COM362 Signals and Systems for Computer Engineers C 3 2 4 6
COM339 Programming Language Concepts C 3 0 3 5
MTH251 Probability and Statistics C 3 0 3 6
COM344 Automata Theory C 3 0 3 5
CAR100 Career Planning C 2 0 0 2
Total 17 2 16 30

6th Semester

CODE COURSE NAME C/E T P C E
AII351 Embedded Systems C 3 2 4 5
AII303 Data Communications and Networking C 3 2 4 5
COM333 Operational Research E 3 0 3 5
COM382 Real Time Systems E 3 0 3 5
AII002 Systems Simulation C 3 0 3 5
COM300 Summer Training II C 0 0 0 5
Total 15 4 17 30

7th Semester

CODE COURSE NAME C/E T P C E
COM490 Engineering Design I C 2 2 3 7
AII003 Software Engineering C 3 0 3 6
TE Technical Elective E 3 0 3 5
TE Technical Elective E 3 0 3 5
TE Technical Elective E 3 0 3 5
CHC100 Cyprus: History and Culture E 2 0 0 2
Total 16 2 15 30

8th Semester

CODE COURSE NAME C/E T P C E
COM491 Engineering Design II C 2 2 3 7
AII426 Economics For Engineers E 3 0 3 6
FE Free Elective E 3 0 3 5
TE Technical Elective E 3 0 3 5
TE Technical Elective E 3 0 3 5
AII010 Safety in Informatics E 2 0 3 2
Total 16 2 18 30
Total No. of Courses52
Total No. of Electives13
Total No. of Credits145
Percentage of Electives25
Total ECTS240
Previous Total No. of Credits147
New Total No. of Credits145
Previous Total ECTS242
New Total ECTS240
C/E: Compulsory/ElectiveT: Hours of Theoretical Study
P: Hours of Practice/LabE: ECTS
C: Credits

ELECTIVE COURSE

CODE COURSE NAME T P C E
Technical Electives
AII401 Microprocessor Systems 3 0 3 5
AII402 Computer Graphics 3 0 3 5
COM410 Parallel Computer Architecture 3 0 3 5
COM414 Digital Control Systems 3 0 3 5
COM416 Computer Networks 3 0 3 5
AII404 Neural Networks 3 0 3 5
AII405 Computer Hardware 3 0 3 5
AII406 System Programming 3 0 3 5
COM430 Programming Languages I 3 0 3 5
AII407 Programming Languages II 3 0 3 5
AII005 İnternet Programlama 3 0 3 5
AII408 Advanced Object Oriented Programming 3 0 3 5
AII409 Object Oriented Programming II 3 0 3 5
COM447 Advanced Operating System 3 0 3 5
AII411 Digital Signal Processing 3 0 3 5
AII412 Database Applications 3 0 3 5
AII413 Introduction to Artificial Intelligence 3 0 3 5
COM452 Introduction to Parallel Computing 3 0 3 5
AII415 Decision Making 3 0 3 5
COM454 Advanced Computer Architecture and Organization 3 0 3 5
AII417 Mobile Computing 3 0 3 5
AII419 Digital Image Processing 3 0 3 5
COM471 Hardware Design using FPGAs 3 0 3 5
AII006 Web Design and Programming 3 0 3 5
AII007 Multimedia Systems 3 0 3 5
AII435 Mechatronics 3 0 3 5
AII423 Robotic Systems 3 0 3 5
AII445 Introduction to Machine Learning 3 0 3 5
AII439 Occupational Safety (Elective) 2 0 3 3
Restricted Electives
MTH323 Numerical Analysis 3 0 3 4
COM315 Algoritms 3 0 3 4
AII217 Microbiology 3 0 3 4
BME102 Biochemistry 3 0 3 4
Free Electives
AII427 Management for Engineers 3 0 3 5
BME102 One of Technical Electives 3 0 3 5

Mission – Vision
Program Information
Qualification Awarded

The students who successfully complete the program are awarded the degree of Bachelor of Science in Artificial Intelligence Engineering.

Level of Qualification

This is a First Cycle (Bachelor’s Degree) program.

Specific Admission Requirements

In the framework of the regulations set by Higher Education Council of Turkey (YÖK), student admission for this undergraduate program is made through a university entrance examination called YKS. Following the submission of students’ academic program preferences, Student Selection and Placement Center (ÖSYM) places the students to the relevant program according to the score they get from ÖSYS.

International students are accepted to this undergraduate program according to the score of one of the international exams they take such as SAT, ACT and so on, or according to their high school diploma score.

Exchange student admission is made according to the requirements determined by bilateral agreements signed by NEU and the partner university.

Visiting students can enroll for the courses offered in this program upon the confirmation of the related academic unit. Additionally, they need to prove their English language level since the medium of instruction of the program is English.

Qualification Requirements and Regulations

The students studying in this undergraduate program are required to have a Cumulative Grade Points Average (CGPA) of not less than 2.00/4.00 and have completed all the courses with at least a letter grade of DD/S in the program in order to graduate. The minimum number of ECTS credits required for graduation is 251. It is also mandatory for the students to complete their compulsory internship in a specified duration and quality.

Recognition of Prior Learning

At Near East University, full-time students can be exempted from some courses within the framework of the related bylaws. If the content of the course previously taken in another institution is equivalent to the course offered at NEU, then the student can be exempted from this course with the approval of the related faculty/graduate school after the evaluation of the course content.

Profile of the Program

The program's goal is to equip its graduates with both the fundamental scientific principles that underpin the key artificial intelligence technologies in use today and the engineering skills that enable those principles to be applied in practice. Upon graduation, students should be equipped to pursue a career as artificial intelligence professionals or, if they so wish, to pursue further academic studies. The graduates will be professionals who can be flexible and integrate in a relatively short time into a wide-range of different sectors of the industry.

Program Outcomes
  • To have adequate knowledge in Mathematics, Science and Artificial intelligence Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.
  • Gains the ability to understand the basic algorithms of artificial intelligence-based systems and understand the basic concepts of artificial intelligence-based systems.
  • Gain knowledge of problem solving and planning.
  • To be able to design artificial intelligence based systems.
  • To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Artificial Intelligence Engineering applications; to be able to use information technologies effectively.
  • Intelligent agents, search methods in problem solving, informed and uninformed search methods, exploration methods, constraint supply problems, game playing, knowledge and reasoning, primary logic, knowledge representation, learning.
  • To be able to solve real life problems involving large and complex data sets using mathematical computational and artificial intelligence techniques
  • To have knowledge about global and social impact of Artificial Intelligence Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Artificial Intelligence Engineering solutions.
  • To be aware of ethical behaviour, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.
  • To be able to represent information using different techniques
  • To be able to the appropriate scanning technique to achieve the desired goals.
  • To be able to collect data in the area of Artificial Intelligence Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1)
  • To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.
Course and Program Outcomes Matrix
Occupational Profiles of Graduates

Graduates of Artificial Intelligence Engineering program may work as a AI/Machine Learning Engineer or Developer. Also they can work in the Healthcare, Customer service, Airline industry, Cybersecurity, Education, Marketing, Retail and E-Commerce, Financial Markets and Services departments.

Access to Further Studies

The students graduating from this program may apply to graduate programs.

Course Structure Diagram with Course Credits
Exam Regulations, Assessment and Grading
Graduation Requirements

In order to graduate from this undergraduate program, the students are required;

  • to succeed in all of the courses listed in the curriculum of the program by getting the grade of at least DD/S with a minimum of 251 ECTS
  • to have a Cumulative Grade Point Average (CGPA) of 2.00 out of 4.00
  • to complete their compulsory internship in a specified duration and quality.
Mode of Study

This is a full time program.

Program Director (or Equivalent)

Prof. Dr. Fadi AL-TURJMAN, Head of Department, Faculty of Engineering, Near East University

Evaluation Questionnaires
  • Evaluation Survey
  • Graduation Survey
  • Satisfaction Survey