Chairman’s Welcome Message
Courses
1st Semester 2nd Semester 3rd Semester 4th Semester 5rd Semester 6th Semester 7th Semester 8th Semester ELECTIVE COURSE
CODE
COURSE NAME
C/E
T
P
C
E
MTH113
LINEAR ALGEBRA
C
3
0
3
5
AII102
PROGRAMMING AND PROBLEM SOLVING
C
3
2
4
5
ENG101
ENGLISH I
C
3
0
2
5
MTH101
CALCULUS I
C
4
0
4
5
PHY101
GENERAL PHYSICS I
C
3
2
4
5
CAM100
CAMPUS ORIENTATION
C
2
0
0
5
CHM101
GENERAL CHEMISTRY I
C
3
2
4
5
Total
21
6
19
30
CODE
COURSE NAME
C/E
T
P
C
E
AII104
DISCRETE STRUCTURES
C
3
0
3
5
ENG102
ENGLISH II
C
3
0
2
3
MTH102
CALCULUS II
C
4
0
4
6
PHY102
GENERAL PHYSICS II
C
3
2
4
6
AII108
OBJECT ORIENTED PROGRAMMING
C
2
2
3
6
YIT101
TURKISH FOR FOREIGNERS I
C
2
0
2
2
GEC351
21st CENTURY SKILLS
C
2
0
0
2
Total
19
4
18
30
CODE
COURSE NAME
C/E
T
P
C
E
DAE001
ADVANCED ALGEBRA AND CALCULUS
C
3
2
4
6
AII201
DATA STRUCTURES & ALGORITHMS
C
3
2
4
6
DAE003
INFORMATION THEORY
E
3
0
4
4
MTH 201
DIFFERENTIAL EQUATIONS
C
4
0
4
6
DAE002
INTRODUCTION TO AUDIOVISUAL PROCESSING
E
3
0
3
4
AIT 103
ATATÜRK PRINCIPLES AND REFORMS I
C
2
0
2
2
YIT102
TURKISH FOR FOREIGNERS II
C
2
0
2
2
Total
20
4
23
30
CODE
COURSE NAME
C/E
T
P
C
E
AII202
DATABASE MANAGEMENT SYSTEMS
C
4
0
4
5
DAE004
DATA ENGINEERING THEORY
E
3
2
3
5
DAE005
SIGNALS AND SYSTEMS
C
4
0
4
4
MTH251
PROBABILITY AND STATISTICS
C
3
0
3
6
AIT104
ATATÜRK PRINCIPLES AND REFORMS II
C
2
0
2
2
AIE299
SUMMER TRAINING I
C
0
2
0
6
CHC100
CYPRUS HISTORY AND CULTURE
E
2
0
0
2
Total
18
4
16
30
CODE
COURSE NAME
C/E
T
P
C
E
DAE007
PROBABILITY AND STATISTICS 2
C
3
0
3
5
DAE006
MACHINE LEARNING FOR SATELLITE IMAGERY
E
2
2
3
5
ENG201
ORAL COMMUNICATION SKILLS
C
3
0
3
4
DAE008
PRESCRIPTIVE ANALYTICS I
E
3
0
3
5
AII439
OCCUPATIONAL HEALTH AND SAFETY I
C
2
0
2
4
DAE009
SYSTEMS ENGINEERING
E
3
0
3
5
CAR100
CAREER PLANNING
C
2
0
0
2
Total
18
2
17
30
CODE
COURSE NAME
C/E
T
P
C
E
DAE011
MACHINE LEARNING 1
E
3
0
4
5
DAE012
MATHEMATICAL OPTIMIZATION
E
3
2
4
5
DAE013
PARALLELISM AND DISTRIBUTED SYSTEMS
E
3
0
4
5
DAE014
ADVANCED DATABASES
E
4
2
4
5
AIE399
SUMMER TRAINING II
C
0
0
0
5
DAE010
PRESCRIPTIVE ANALYTICS II
E
3
0
4
5
Total
16
4
20
30
CODE
COURSE NAME
C/E
T
P
C
E
DAE015
MACHINE LEARNING 2
E
3
0
3
5
DAE016
ENTREPRENEURSHIP AND INNOVATION
E
3
0
3
4
DAE018
SENIOR ADVANCED DESIGN PROJECT I
C
4
2
4
6
TE
TECHNICAL ELECTIVE
E
3
0
3
5
TE
TECHNICAL ELECTIVE
E
3
0
3
5
DAE017
INFORMATION RETRIEVAL AND ANALYSIS
E
3
2
4
5
Total
19
4
20
30
CODE
COURSE NAME
C/E
T
P
C
E
AII429
ENGINEERING ETHICS
C
3
0
3
5
DAE019
SENIOR ADVANCED DESIGN PROJECT II
C
3
0
3
5
DAE020
INFORMATION VISUALIZATION
E
3
0
3
4
TE
TECHNICAL ELECTIVE
E
3
0
3
5
TE
TECHNICAL ELECTIVE
E
3
0
3
5
DAE021
IMAGE PROCESSING AND MACHINE VISION
E
3
0
3
4
AII440
OCCUPATIONAL HEALTH AND SAFETY II
C
2
0
3
2
Total
18
0
21
30
Total No. of Courses 53 Total No. of Electives 21 Total No. of Credits 156 Percentage of Electives 39 Total ECTS 240 Previous Total No. of Credits 163 New Total No. of Credits 158 Previous Total ECTS 240 New Total ECTS No change 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
AII419
IMAGE PROCESSING
2
2
3
5
AII415
DECISION MAKING
2
2
3
5
AIE411
ADVANCED DATA ANALYSIS
2
2
3
5
AIE412
INFORMATION RETRIEVAL AND WEB SEARCH
2
2
3
5
AIE413
HUMAN-ROBOT INTERACTION
2
2
3
5
AIE414
DEEP REINFORCEMENT LEARNING AND CONTROL
2
2
3
5
AIE415
MOBILE ROBOT PROGRAMMING
2
2
3
5
AIE416
AUTONOMOUS AGENTS
2
2
3
5
AIE417
INTRODUCTION TO QUANTUM COMPUTING
2
2
3
5
AIE418
COMPUTER ANIMATION & VISUALIZATION
2
2
3
5
AIE419
ALGORITHMIC GAME THEORY AND ITS APPLICATIONS
2
2
3
5
AIE420
FUZZY SYSTEMS
2
2
3
5
AIE458
AI AND INTERNET OF THINGS
2
2
3
5
AIE457
AI AND CLOUD COMPUTING
2
2
3
5
DAE022
BIG DATA SYSTEMS
2
2
3
5
DAE023
DATA SECURITY AND PRIVACY FOR ANALYTICS
2
2
3
5
DAE024
BUSINESS ANALYTICS
2
2
3
5
DAE025
HEALTH INFORMATICS
2
2
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