Artificial Intelligence Master's Program with Thesis
General Description
Interdisciplinary Artificial Intelligence Master´s Program was launched and started education in the Fall Semester of 2021-2022. The program has been designed with an interdisciplinary content and is the first master´s program of its kind opened in Turkey in this field. In addition to fundamental courses in the field of Artificial Intelligence, it also includes courses from Master´s programs in Computer Engineering, Industrial Engineering, Mechanical Engineering, and Electronic Engineering.
Upon successful completion of the Artificial Intelligence Master´s Program and fulfillment of program requirements, a Master´s degree in Artificial Intelligence is conferred.
Second Cycle
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Specific Admission Requirements
To be eligible to apply for the Master´s program, candidates must have a minimum score of 55 or higher on the ALES (Academic Personnel and Graduate Education Entrance Exam) or an equivalent exam, as determined by the Senate. For Master´s applications, a foreign language proficiency score is not required; however, in cases where candidates have equal scores, those with a higher English proficiency score will be given preference. The program is interdisciplinary and accepts students with a bachelor´s degree in Computer Engineering, Industrial Engineering, Electronic Engineering, Mechatronic Engineering, Electrical and Electronics Engineering, Mechanical Engineering, and Automotive Engineering.
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Specific arrangements for the recognition of prior learning
The provisions in “Regulation on Transfer among Associate and Undergraduate Degree Programs, Double Major, and Subspecialty and the Principals of Credit Transfer among Institutions in Higher Education Institutions” are applied.
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Qualification Requirements and Regulations
Students who are enrolled in the graduate programs of the Department or other related Departments must have a minimum of eight courses, including at least one seminar course, from the courses available in the graduate programs, with a total of at least 120 ECTS credits, including a seminar course and a thesis study, provided that one academic semester is not less than 60 ECTS credits. Upon successful defense of the thesis before a jury consisting of faculty members, students are awarded a Master´s degree in Artificial Intelligence Engineering. To be considered successful in courses, excluding seminars, a weighted average grade of at least 70 out of 100 must be achieved. Additionally, the student must fulfill the publication or scientific activity requirement determined by the Senate to be eligible for graduation.
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Profile of The Programme
The Artificial Intelligence Master´s program offers interdisciplinary education, featuring a faculty team composed of 7 instructors from various departments. In addition to the core faculty members of the Artificial Intelligence Master´s program, external instructors from different academic disciplines also contribute by teaching courses and providing academic guidance to the students.
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Key Learning Outcomes & Classified & Comparative
1.
Developing the skill of comprehending and applying mathematics, computer sciences, statistics, and engineering sciences involved in artificial intelligence techniques.
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2.
Developing the ability to apply artificial intelligence methods to a new domain.
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3.
Developing the competence to track contemporary issues and research topics related to artificial intelligence within the scope of continuous learning.
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4.
Developing the skill to understand and analyze the impacts of artificial intelligence-based solutions on science, society, and the business world.
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5.
Developing the ability to share research through oral, written, and electronic means.
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6.
Developing the capability to conduct artificial intelligence studies in a professional, legal, and ethical manner and fostering a lifelong learning consciousness.
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7.
Developing the capacity to conduct original and independent research.
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8.
Developing the skill to transfer acquired knowledge through teaching.
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9.
Fostering the capability to participate in teamwork and take individual responsibility when necessary.
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Occupational Profiles of Graduates With Examples
Graduates of the Artificial Intelligence Master´s program will have the opportunity to work in companies operating in manufacturing and service sectors such as software, automotive, machinery, electronics, telecommunications, defense, and medical industries.
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Access to Further Studies
Candidates who successfully complete their master´s education, upon meeting the application and registration requirements for doctoral programs, may pursue further education in doctoral programs.
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Examination Regulations, Assessment and Grading
"The Graduate Education and Training Regulation of Uludağ University" is applied for postgraduate education.
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Graduation Requirements
To successfully complete the Artificial Intelligence Master´s program, a minimum of 120 ECTS credits must be obtained. This includes mandatory and elective courses specified by the department chairmanship, comprising at least eight courses, a seminar course, expert field courses taken each semester, and successful completion of a thesis.
Full-Time
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Address and Contact Details
Program Başkanı:
Prof. Dr. Tülin İNKAYA
Tel:+90 (224) 294 2605
E-posta: tinkaya@uludag.edu.tr
İdari personel:
Zehra Yılmaz
0 (224) 294 2797
yapayzeka@uludag.edu.tr
Adres:
Bursa Uludağ Üniversitesi Mühendislik Fakültesi Endüstri Mühendisliği Bölümü Görükle Kampüsü 16059 BURSA
The courses are conducted in 18 classrooms shared with the Departments of Computer Engineering, Industrial Engineering, Electronic Engineering, and Mechanical Engineering. These classrooms possess the essential features for a contemporary engineering education. All of these classrooms are equipped with air conditioning and projection devices. Additionally, there are computer laboratories dedicated to educational and research activities.
1. Semester |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
BM5103 |
ALGORITHMS |
Compulsory |
3 |
0 |
0 |
6 |
YZ5181 |
ADVANCED TOPICS IN MA THESIS I |
Compulsory |
4 |
0 |
0 |
5 |
YZ5191 |
THESIS CONSULTING I |
Compulsory |
0 |
1 |
0 |
1 |
|
Click to choose optional courses.
|
|
|
|
|
18 |
Total |
|
30 |
2. Semester |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
FEN5000 |
RESEARCH TECHNIQUES AND PUBLICATION ETHICS |
Compulsory |
2 |
0 |
0 |
2 |
YZ5172 |
SEMINAR |
Compulsory |
0 |
2 |
0 |
4 |
YZ5182 |
ADVANCED TOPICS IN MSC THESIS II |
Compulsory |
4 |
0 |
0 |
5 |
YZ5192 |
THESIS CONSULTING II |
Compulsory |
0 |
1 |
0 |
1 |
|
Click to choose optional courses.
|
|
|
|
|
18 |
Total |
|
30 |
3. Semester |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
YZ5183 |
ADVANCED TOPICS IN MSC THESIS III |
Compulsory |
4 |
0 |
0 |
5 |
YZ5193 |
THESIS CONSULTING III |
Compulsory |
0 |
1 |
0 |
25 |
Total |
|
30 |
4. Semester |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
YZ5184 |
ADVANCED TOPICS IN MSC THESIS IV |
Compulsory |
4 |
0 |
0 |
5 |
YZ5194 |
THESIS CONSULTANTS IV |
Compulsory |
0 |
1 |
0 |
25 |
Total |
|
30 |
1. Semester Optional Courses |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
BM5113 |
COMPUTER VISION |
Optional |
3 |
0 |
0 |
6 |
BM5115 |
NATURAL LANGUAGE PROCESSING |
Optional |
3 |
0 |
0 |
6 |
BM5121 |
IMAGE PROCESSING AND APPLICATIONS |
Optional |
3 |
0 |
0 |
6 |
BM5701 |
INTRODUCTION TO INFORMATION RETRIEVAL |
Optional |
3 |
0 |
0 |
6 |
ELN5415 |
PATTERN RECOGNITION |
Optional |
3 |
0 |
0 |
6 |
ELN5503 |
NUMERICAL COMPUTING AND PROGRAMMING |
Optional |
3 |
0 |
0 |
6 |
END5123 |
HEURISTIC ALGORITHMS |
Optional |
3 |
0 |
0 |
7,5 |
END5151 |
STATISTICAL DATA ANALYSIS |
Optional |
3 |
0 |
0 |
7,5 |
END5161 |
DATA MINING |
Optional |
3 |
0 |
0 |
7,5 |
MAK5217 |
COMPUTER GRAPHICS |
Optional |
3 |
0 |
0 |
6 |
MAK5265 |
STRUCTURAL DESIGN AND OPTIMIZATION IN MECHANICAL ENGINEERING |
Optional |
3 |
0 |
0 |
6 |
YIT5017 |
METAMODELING AND ARTIFICIAL INTELLIGENCE APPLICATIONS IN ENGINEERING |
Optional |
3 |
0 |
0 |
6 |
2. Semester Optional Courses |
Course Code |
Course Title |
Type of Course |
T1 |
U2 |
L3 |
ECTS |
BM5116 |
ARTIFICIAL INTELLIGENCE THEORY |
Optional |
3 |
0 |
0 |
6 |
BM5130 |
BIOINFORMATIC ALGORITHM |
Optional |
3 |
0 |
0 |
6 |
BM5138 |
STATISTICAL METHODS IN NATURAL LANGUAGE PROCESSING |
Optional |
3 |
0 |
0 |
6 |
BM5142 |
INTRODUCTION TO DATA MINING |
Optional |
3 |
0 |
0 |
6 |
ELN5418 |
PATTERN RECOGNITION WITH NEURAL NETWORKS |
Optional |
3 |
0 |
0 |
6 |
END5101 |
MATHEMATICAL PROGRAMMING |
Optional |
3 |
0 |
0 |
7,5 |
END5124 |
CONSTRAINT PROGRAMMING |
Optional |
3 |
0 |
0 |
7,5 |
END5162 |
APPLIED MACHINE LEARNING |
Optional |
3 |
0 |
0 |
7,5 |
MAK5268 |
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN MECHANICAL ENGINEERING |
Optional |
3 |
0 |
0 |
6 |