ECTS Information Guide

Main Page

Information on the Institution

General Description of the Institution Address of Namık Kemal University Academic Calendar Academic Authorities Recognition of Prior Learning Recognition of Study Abroad List of Programmes Offered at TNKÜ General Admission Requirements General Registration Procedures ECTS Credit Allocation Arrangements for Academic Guidance

Degrees and Programmes

Doctorate(Third Cycle) Master's Degree(Second Cycle) Bachelor's Degree(First Cycle) Associate(Short Cycle)

General Information For Students

About Trakya and Tekirdağ Cost of Living Accommodation Meals Medical Facilities Facilities for Students with Special Needs Insurance Financial Support for Students Student Affairs Office Learning Facilities International Programmes Practical Information for Exchange Students Language Courses Internship Sports and Leisure Facilities Student Clubs Useful Phone Numbers

Diploma Supplement

National Qualifications

Computer Engineering(YL) Master Degree With a Thesis Program

Academic Unit Presenting the Program

Computer Engineering(YL)

Program Director

Program Type

Master Degree With a Thesis Program

Level of Degree Earned

Graduate (Master’s Degree).

Degree Earned

Post graduate diploma is given to the graduates who successfully complete the post graduate study at the concerning department depending upon the graduate school of natural and applied sciences.

Education Type

Tam Zamanlı

Registration Acceptance Conditions

(1) Candidates who apply for admission to a master programme should hold a valid bachelor’s degree and, except the applicants to the Department of Music, a minimum score of 55 from the Selection Examination for Academic Personnel and Graduate Studies (ALES) administered by the Student Selection and Placement Centre (ÖSYM). Instead of ALES score, candidates may choose to submit the scores of other internationally accepted examinations whose validity and equivalency are determined by the University Senate. (2) The final admission score is determined as the total sum of %10 of the undergraduate GPA, %50 of ALES score and %40 of the grade received in the entrance examination which is conducted by a jury determined by and representing the Department. The final admission score should be at least 65. The number of accepted students is decided prior to the admission and the successful applicants are shortlisted according to the scores starting with the highest ones.

Recognition of Prior Learning

A student who has successfully completed at least one semester in a comparable master programme at another accredited institution is eligible as a lateral transfer. Lateral transfers are generally admitted after being evaluated on a case by case basis and upon the decision of the administration of the Department and the Graduate School.

Degree Requirements and Rules

to take a minimum of 7 courses with a minimum of 21 local credits.
to succeed in all the courses with a letter grade of at least CC/S
to prepare and defend a master's dissertation
to have a Cumulative Grade Point Average of at least 2.00/4.00 with a minimum of 120 ECTS credits.

Program Profile

Occupational Profiles of Graduates

Access To Upper Degree

Upon successful completion of their master programme, the students are encouraged to embark on further academic studies on the graduate level (doctoral programme) on condition of having received the required score in ALES exam, possessing sufficient knowledge of English or another foreign language, and being successful in the entrance examination.

Exams, Assessment and Grading

For a student to have successfully completed the master programme, the GPA should be at least 65.

Grades

The grading system to evaluate the student performance is signified by the values in the chart below. For each course students are graded by letters. Letter grades, coefficients and ratios are as follows:

Grade	Letter Grade	Local Grade	Status
90-100	AA	4.00	Pass
85-89	BA	3.50	Pass
80-84	BB	3.00	Pass
75-79	CB	2.50	Pass
65-74	CC	2.00	Pass
0-64	FF	1.50	Fail

Graduation Requirements

Requirements for graduation are as stated in “Principles Regarding the Post graduate Degree” part.

Teaching Methods

Teaching methods are determined so as to improve skills, such as teaching-learning strategies, self-discipline, life-long learning, observation, sharing knowledge, presentation, critical thinking, teamwork, effective use of informatics.

Moreover, the choice of teaching methods pays heed to supporting students with different skills. The teaching methods used in the program are listed below*:

TEACHING METHODS*	LEARNING ACTIVITIES	MEANS
Course	Listening and interpretation	Standard classroom technologies, multimedia devices, projector, computer, overhead projector
Discussion Course	Listening and interpretation, observation/situation handling, critical thinking, question development	Standard classroom technologies, multimedia devices, projector, computer, overhead projector
Special Support / Structural Examples	Special skills planned beforehand
Playing a Role / Drama	Special skills planned beforehand	Standard classroom technologies, special equipment
Problem Solving	Special skills planned beforehand
Case Study	Special skills planned beforehand
Brainstorming	Listening and interpretation, observation/situation handling, critical thinking, question development, team work	Standard classroom technologies, multimedia devices, projector, computer, overhead projector
Small Group Discussion	Listening and interpretation, observation/situation handling, critical thinking, question development	Standard classroom technologies, multimedia devices, projector, computer, overhead projector
Presentation	Listening and interpretation, observation/situation handling	Real or virtual environment suitable for observation
Simulation	Listening and interpretation, observation/situation handling, informatics skills	Real or virtual environment suitable for observation
Seminar	Research – lifelong learning, writing, reading, informatics, listening and interpretation, management skills	Standard classroom technologies, multimedia devices, projector, computer, overhead projector, special equipment
Group Study	Research – lifelong learning, writing, reading, informatics, critical thinking, question development, management skills, team work
Field / Land Study	Observation / situation handling, research – lifelong learning, writing, reading
Laboratory	Observation/situation handling, informatics, management skills, team work	Special equipment
Homework	Research – lifelong learning, writing, reading, Informatics	Internet database, library database, e-mail
Oral Exam
Survey and Questionnaire Study	Research – lifelong learning, writing, reading
Panel	Listening and interpretation, observation/situation handling	Standard classroom technologies, multimedia devices, projector, computer, overhead projector, special equipment
Guest Speaker	Listening and interpretation, observation/situation handling	Standard classroom technologies, multimedia devices, projector, computer, overhead projector, special equipment
Student Club Activity / Projects	Observation/situation handling, critical thinking, question development, team work, research – lifelong learning, writing, reading, management skills, special skills planned beforehand

*One or more of the listed methods can be used depending on the specificity of the course.

Program Outcomes

1-The ability to generate different solutions based on theoretical foundations of analysis and design, and compare them in terms of their benefits and costs, and implement the most appropriate solution
2-The ability to conduct in-depth research on the topic of study in the field of Computer Science and Engineering, evaluate the acquired knowledge, and apply it effectively
3-Comprehensive knowledge about current techniques and limitations used in computer engineering.
4-The ability to follow scientific developments and renew oneself.
5-The ability to collect scientific data, evaluate it, and interpret it.
6-Ability to integrate and collaborate with teams from different disciplines to solve a problem and generate a solution
7-Effective verbal and written communication of problem-solving skills and scientific knowledge
8-Ability to identify the most suitable tools for a given problem
9-Ability to plan projects and manage time effectively, and take precautions against potential risks.
10-Ability to conduct scientific work with consideration for societal, environmental, and ethical values
11-Ability to work as a researcher in national or international R&D-focused institutions (universities, companies' R&D centers and research institutes, etc.) or establish their own business in the field of computer engineering, use their acquired research skills and knowledge of scientific advancements in the field.

Curriculum

Course
Computer Engineering(YL)
2023-2024 Fall Semester

Course Code	Course Name	Browse	T	A	ECTS
LÜ-FBE-04	Scientific Research Techniques and Scientific Ethics		3	0	5
BLM5119	Software Project Management		3	0	8
BLM5118	Software Quality and Testing Techniques		3	0	8
LÜ-FBE-01	Special Topics		8	0	10
Elective	2022-2023 GÜZ(BİLGİSAYAR)				45
LÜ-BMB-10	Advanced Data Mining and Big Data		3	0	5
LÜ-BMB-20	Advanced Topies in İmage Processing and Applications		3	0	5
LÜ-BMB-19	Deep Learning		3	0	5
LÜ-BMB-01	Introduction to Cryptology and Computer Network Security		3	0	5
LÜ-BMB-04	Metaheuristic Algorithms		3	0	5
LÜ-BMB-22	Natural Language Processing		3	0	5
LÜ-BMB-08	Programming Methodology in Python		3	0	5
Total ECTS:					76
2023-2024 Spring Term

Course Code	Course Name	Browse	T	A	ECTS
LÜ-FBE-02	MSc. Seminar		0	2	5
LÜ-FBE-04	Scientific Research Techniques and Scientific Ethics		3	0	5
LÜ-FBE-01	Special Topics		8	0	10
LÜ-FBE-01	Special Topics		8	0	10
Elective	2023-2024 bahar bilgisayar 2()				45
LÜ-BMB-11	Artificial Intelligence Techniques and Machine Learning		3	0	5
LÜ-BMB-05	Compressed Pattern Matching		3	0	5
LÜ-BMB-03	Cryptology and Computer Network Security		3	0	5
LÜ-BMB-02	Cryptology and Computer Network Security		3	0	5
LÜ-BMB-06	Design of Simulation Models		3	0	5
LÜ-BMB-12	High Performance Computing		3	0	5
LÜ-BMB-09	Information Retrieval and Web Search		3	0	5
Total ECTS:					75
Total ECTS(Year):					151
Thesis
2023-2024 Fall Semester

Course Code	Course Name	Browse	T	A	ECTS
LÜ-FBE-01	Special Topics		8	0	10
LÜ TEZ	Thesis		0	0	20
Total ECTS:					30
2023-2024 Spring Term

Course Code	Course Name	Browse	T	A	ECTS
LÜ-FBE-01	Special Topics		8	0	10
LÜ TEZ	Thesis		0	0	20
Total ECTS:					30
Total ECTS(Year):					60

Matrix of Course - Program Outcomes

LÜ-FBE-04 Scientific Research Techniques and Scientific Ethics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-FBE-01 Special Topics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-BMB-10 Advanced Data Mining and Big Data
#
	5	3	3	3	5	3	4	2	2	1	4
	3	3	3	3	3	3	2	4	2	1	3
	3	4	3	3	4	3	2	3	2	1	5
	3	3	3	3	5	4	2	3	3	1	4
	3	3	3	3	4	3	2	5	2	1	3
	5	3	3	3	5	3	2	3	2	2	4
	3	3	3	5	3	3	2	3	2	2	3
	3	3	5	4	4	3	2	4	2	2	5
	4	3	3	3	5	4	2	3	2	2	3
	3	3	5	3	5	4	3	3	2	3	4
	4	4	4	3	4	4	4	3	2	2	3
	4	4	3	3	5	4	2	3	2	2	4

LÜ-BMB-20 Advanced Topies in İmage Processing and Applications
#
	3	4	3	3	3	2	4	3	3	0	0
	4	4	4	4	2	2	3	3	3	0	0
	3	4	4	3	2	2	3	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	3	3	3	3	3	4	4	4	0	0
	3	3	4	3	3	3	4	4	4	0	0

LÜ-BMB-19 Deep Learning
#
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4

LÜ-BMB-01 Introduction to Cryptology and Computer Network Security
#
	4	5	3	4	3	4	4	3	5	4	4
	4	5	3	4	3	4	4	3	5	4	4
	4	5	3	4	3	4	4	3	5	4	4
	4	5	3	4	3	4	4	3	5	4	4
	4	5	3	4	3	4	4	3	5	4	4

LÜ-BMB-04 Metaheuristic Algorithms
#
	3	4	3	4	3	5	3	3	5	3	5
	3	4	3	4	3	5	3	3	5	3	5
	3	4	3	4	3	5	3	3	5	3	5
	3	4	3	4	3	5	3	3	5	3	5
	3	4	3	4	3	5	3	3	5	3	5

LÜ-BMB-22 Natural Language Processing
#
	2	4	5	5	5	3	4	4	3	3	0

LÜ-BMB-08 Programming Methodology in Python
#
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4
	5	2	3	1	5	2	4	2	4

LÜ-FBE-02 MSc. Seminar
#
	3	3	4	3	4	5	5	3	3	4	4
	3	3	4	3	4	5	5	3	3	4	4
	3	3	4	3	4	5	5	3	3	4	4
	3	3	4	3	4	5	5	3	3	4	4

LÜ-FBE-04 Scientific Research Techniques and Scientific Ethics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-BMB-11 Artificial Intelligence Techniques and Machine Learning
#
	1	4	3	4	4	1	2	1	1	1	2
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	3	3
	1	4	3	4	4	1	2	1	1	4	3
	1	4	3	4	4	1	2	1	1	4	3

LÜ-BMB-05 Compressed Pattern Matching
#
	4	2	4	3	2	4	3	4	4	3	4
	4	4	4	4	3	4	3	3	3	2	3
	4	4	2	2	4	2	4	3	4	2	4
	4	3	3	4	2	3	3	2	3	3	3
	3	4	3	4	3	3	2	2	4	4	4

LÜ-BMB-03 Cryptology and Computer Network Security
#
	5	5	5	4	4	4	4	4	4	3	3
	5	5	5	4	4	4	4	4	4	3	3
	5	5	5	4	4	4	4	4	4	3	3
	5	5	5	4	4	4	4	4	4	3	3

LÜ-BMB-02 Cryptology and Computer Network Security
#
	4	4	4	0	4	4	5	4	4	3	3
	4	3	5	0	3	4	4	5	4	5	4
	4	4	3	2	3	4	4	5	4	3	4
	4	5	3	4	3	4	4	5	4	4	4

LÜ-BMB-06 Design of Simulation Models
#
	4	4	3	4	4	3	3	3	2
	4	4	3	4	4	3	3	3	2
	4	4	3	4	4	3	3	3	2
	4	4	3	4	4	3	3	3	2
	4	4	3	4	4	3	3	3	2

LÜ-BMB-12 High Performance Computing
#
	2	4	3	4	4	3	2	3	1	1	4
	3	3	3	3	3	3	2	3	2	1	3
	1	3	2	4	3	2	2	3	2	1	4
	2	4	3	4	3	3	2	3	2	1	3
	3	3	4	4	4	3	2	3	1	1	3
	2	3	3	3	5	3	3	4	2	1	3
	2	4	3	3	3	3	3	3	1	1	3
	2	4	4	3	3	3	2	2	1	2	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	4	3	3	2	3	1	2	3
	5	4	4	4	3	3	2	3	2	2	3

LÜ-BMB-09 Information Retrieval and Web Search
#
	4	5	2	4	3	3	3	2	2
	4	5	2	4	3	3	3	2	2
	4	5	2	4	3	3	3	2	2
	4	5	2	4	3	3	3	2	2
	4	5	2	4	3	3	3	2	2
	4	5	2	4	3	3	3	2	2

LÜ TEZ Thesis
#
	5	5	5	5	4	5	4	4	5	3	5
	5	4	5	5	4	4	2	5	2	2	5
	3	3	4	4	3	4	4	4	5	2	5
	4	5	2	3	4	4	5	2	4	3	5
	4	5	5	5	3	4	3	5	3	3	5

LÜ TEZ Thesis
#
	3	4	4	3	5	3	5	3	4	5	4
	3	3	4	3	5	3	5	5	3	5	4
	3	3	3	4	4	3	4	4	5	3	4
	4	3	3	4	4	4	5	5	3	3	4

LÜ-BMB-10 Advanced Data Mining and Big Data
#
	5	3	3	3	5	3	4	2	2	1	4
	3	3	3	3	3	3	2	4	2	1	3
	3	4	3	3	4	3	2	3	2	1	5
	3	3	3	3	5	4	2	3	3	1	4
	3	3	3	3	4	3	2	5	2	1	3
	5	3	3	3	5	3	2	3	2	2	4
	3	3	3	5	3	3	2	3	2	2	3
	3	3	5	4	4	3	2	4	2	2	5
	4	3	3	3	5	4	2	3	2	2	3
	3	3	5	3	5	4	3	3	2	3	4
	4	4	4	3	4	4	4	3	2	2	3
	4	4	3	3	5	4	2	3	2	2	4

LÜ-BMB-20 Advanced Topies in İmage Processing and Applications
#
	3	4	3	3	3	2	4	3	3	0	0
	4	4	4	4	2	2	3	3	3	0	0
	3	4	4	3	2	2	3	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	3	3	3	3	3	4	4	4	0	0
	3	3	4	3	3	3	4	4	4	0	0

LÜ-FBE-04 Scientific Research Techniques and Scientific Ethics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-BMB-11 Artificial Intelligence Techniques and Machine Learning
#
	1	4	3	4	4	1	2	1	1	1	2
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	3	3
	1	4	3	4	4	1	2	1	1	4	3
	1	4	3	4	4	1	2	1	1	4	3

LÜ-BMB-12 High Performance Computing
#
	2	4	3	4	4	3	2	3	1	1	4
	3	3	3	3	3	3	2	3	2	1	3
	1	3	2	4	3	2	2	3	2	1	4
	2	4	3	4	3	3	2	3	2	1	3
	3	3	4	4	4	3	2	3	1	1	3
	2	3	3	3	5	3	3	4	2	1	3
	2	4	3	3	3	3	3	3	1	1	3
	2	4	4	3	3	3	2	2	1	2	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	4	3	3	2	3	1	2	3
	5	4	4	4	3	3	2	3	2	2	3

LÜ-BMB-10 Advanced Data Mining and Big Data
#
	5	3	3	3	5	3	4	2	2	1	4
	3	3	3	3	3	3	2	4	2	1	3
	3	4	3	3	4	3	2	3	2	1	5
	3	3	3	3	5	4	2	3	3	1	4
	3	3	3	3	4	3	2	5	2	1	3
	5	3	3	3	5	3	2	3	2	2	4
	3	3	3	5	3	3	2	3	2	2	3
	3	3	5	4	4	3	2	4	2	2	5
	4	3	3	3	5	4	2	3	2	2	3
	3	3	5	3	5	4	3	3	2	3	4
	4	4	4	3	4	4	4	3	2	2	3
	4	4	3	3	5	4	2	3	2	2	4

LÜ-BMB-20 Advanced Topies in İmage Processing and Applications
#
	3	4	3	3	3	2	4	3	3	0	0
	4	4	4	4	2	2	3	3	3	0	0
	3	4	4	3	2	2	3	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	3	3	3	3	3	4	4	4	0	0
	3	3	4	3	3	3	4	4	4	0	0

LÜ-FBE-04 Scientific Research Techniques and Scientific Ethics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-BMB-11 Artificial Intelligence Techniques and Machine Learning
#
	1	4	3	4	4	1	2	1	1	1	2
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	3	3
	1	4	3	4	4	1	2	1	1	4	3
	1	4	3	4	4	1	2	1	1	4	3

LÜ-BMB-12 High Performance Computing
#
	2	4	3	4	4	3	2	3	1	1	4
	3	3	3	3	3	3	2	3	2	1	3
	1	3	2	4	3	2	2	3	2	1	4
	2	4	3	4	3	3	2	3	2	1	3
	3	3	4	4	4	3	2	3	1	1	3
	2	3	3	3	5	3	3	4	2	1	3
	2	4	3	3	3	3	3	3	1	1	3
	2	4	4	3	3	3	2	2	1	2	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	4	3	3	2	3	1	2	3
	5	4	4	4	3	3	2	3	2	2	3

LÜ-BMB-10 Advanced Data Mining and Big Data
#
	5	3	3	3	5	3	4	2	2	1	4
	3	3	3	3	3	3	2	4	2	1	3
	3	4	3	3	4	3	2	3	2	1	5
	3	3	3	3	5	4	2	3	3	1	4
	3	3	3	3	4	3	2	5	2	1	3
	5	3	3	3	5	3	2	3	2	2	4
	3	3	3	5	3	3	2	3	2	2	3
	3	3	5	4	4	3	2	4	2	2	5
	4	3	3	3	5	4	2	3	2	2	3
	3	3	5	3	5	4	3	3	2	3	4
	4	4	4	3	4	4	4	3	2	2	3
	4	4	3	3	5	4	2	3	2	2	4

LÜ-BMB-20 Advanced Topies in İmage Processing and Applications
#
	3	4	3	3	3	2	4	3	3	0	0
	4	4	4	4	2	2	3	3	3	0	0
	3	4	4	3	2	2	3	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	4	4	3	2	2	4	4	4	0	0
	3	3	3	3	3	3	4	4	4	0	0
	3	3	4	3	3	3	4	4	4	0	0

LÜ-FBE-04 Scientific Research Techniques and Scientific Ethics
#
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1
	1	1	1	1	1	1	1	1	1	1	1

LÜ-BMB-11 Artificial Intelligence Techniques and Machine Learning
#
	1	4	3	4	4	1	2	1	1	1	2
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	1	4
	1	4	3	4	4	1	2	1	1	1	3
	1	4	3	4	4	1	2	1	1	3	3
	1	4	3	4	4	1	2	1	1	4	3
	1	4	3	4	4	1	2	1	1	4	3

LÜ-BMB-12 High Performance Computing
#
	2	4	3	4	4	3	2	3	1	1	4
	3	3	3	3	3	3	2	3	2	1	3
	1	3	2	4	3	2	2	3	2	1	4
	2	4	3	4	3	3	2	3	2	1	3
	3	3	4	4	4	3	2	3	1	1	3
	2	3	3	3	5	3	3	4	2	1	3
	2	4	3	3	3	3	3	3	1	1	3
	2	4	4	3	3	3	2	2	1	2	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	2	3	3	2	3	1	1	3
	2	3	3	4	3	3	2	3	1	2	3
	5	4	4	4	3	3	2	3	2	2	3