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Courses
1st Semester 2nd Semester 3rd Semester 4th Semester 5th Semester 6th Semester 7th Semester 8th Semester ELECTIVE COURSE
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
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
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
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
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
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
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
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 Courses 52 Total No. of Electives 13 Total No. of Credits 145 Percentage of Electives 25 Total ECTS 240 Previous Total No. of Credits 147 New Total No. of Credits 145 Previous Total ECTS 242 New Total ECTS 240 C/E: Compulsory/Elective T: Hours of Theoretical Study P: Hours of Practice/Lab E: ECTS C: Credits
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