English


MECHATRONICS ENGINEERING (ENGLISH) PROGRAMME
COURSE DESCRIPTION
Name of the Course Unit Code Year Semester In-Class Hours (T+P) Credit ECTS Credit
COMPUTATIONAL INTELLIGENCE MEE410 4 8 3+0 3.0 5.0


General Information
Language of Instruction English
Level of the Course Unit Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of the Course Programme Elective
Mode of Delivery of the Course Unit Face-to-face
Work Placement(s) Requirement for the Course Unit Yes
Coordinator of the Course Unit
Instructor(s) of the Course Unit
Assistant(s) of the Course Unit

Prerequisites and/or co-requisities of the course unit
CATEGORY OF THE COURSE UNIT
Category of the Course Unit Degree of Contribution (%)
Fundamental Course in the field % 20
Course providing specialised skills to the main field % 20
Course providing supportive skills to the main field % 20
Course providing humanistic, communication and management skills % 20
Course providing transferable skills % 20

Objectives and Contents
Objectives of the Course Unit The course goal is to make students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI).
Contents of the Course Unit Here belong mainly bottom-up approaches to solutions of (hard) problems based on various heuristics (the so-called soft computing), rather than exact approaches of traditional artificial intelligence based on logic (hard computing). Examples of CI are nature-inspired methods (neural nets, evolutionary algorithms), fuzzy systems, as well as various probabilistic methods under uncertainty (e.g. Bayesian models) and machine learning methods (e.g. reinforcement learning).
Contribution of the Course Intending to Provide the Professional Education After the course the students will be able to conceptually understand the important terms and algorithms of CI, such that they would be able to choose appropriate method(s) for a given task. The theoretical introduction will be complemented by practical examples of task solving.

No
Key Learning Outcomes of the Course Unit
On successful completion of this course unit, students/learners will or will be able to:
1 to make the students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI).
2 bottom-up approaches to solutions of (hard) problems based on various heuristics (soft computing), rather than exact approaches of traditional artificial intelligence based on logic (hard computing).
3 The course goal is to make students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI).

Learning Activities & Teaching Methods of the Course Unit
Learning Activities & Teaching Methods of the Course Unit

Weekly Course Contents and Study Materials for Preliminary & Further Study
Week Topics (Subjects) Preparatory & Further Activities
1 What is computational intelligence, basic concepts, relation to other fields. No file found
2 Rational agents, taxonomy. No file found
3 Types of environment. No file found
4 Feedforward neural networks (perceptrons), No file found
5 supervised learning, classification, function approximation No file found
6 Self-organizing neural networks: feature extraction, data visualization. No file found
7 Midterm exam No file found
8 Inductive learning via observations, decision trees. No file found
9 Statistical learning, probabilistic models. No file found
10 Reinforcement learning I: basic principles and learning methods (TD-learning). No file found
11 Prediction problem. No file found
12 Reinforcement learning II (Q, SARSA), actor-critic, control problem, RL for continuous domain. No file found
13 Evolutionary computation: basic concepts, genetic algorithms. No file found
14 Final Exam No file found

SOURCE MATERIALS & RECOMMENDED READING
1-Craenen B., Eiben A. (2003): Computational Intelligence. In: Encyclopedia of Life Support Sciences, EOLSS Publishers Co.

MATERIAL SHARING
Course Notes No file found
Presentations No file found
Homework No file found
Exam Questions & Solutions No file found
Useful Links No file found
Video and Visual Materials No file found
Other No file found
Announcements No file found

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES
KNOWLEDGE
Theoretical
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 The program will enable students to develop:A broad understanding of the utilization of computers in control and communication; A basic understanding of the principles of motion control; X
2 Ability to identify, define, formulate and solve complex engineering problems; ability to select and implement the appropriate analysis and modeling methods in this respect X
SKILLS
Cognitive
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 Ability to work in the areas of controll, electronics, mechanics and computer systems; Adequate knowledge ability in analysing and designing of complex electro mechanic devices, hardware and software containing systems in which interact with dynamic systems. X
2 Knowledge of applications in business life such as project management, risk management and change management; awareness about entrepreneurship, innovativeness and sustainable development. X
Practical
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 The program will enable students to develop:Creative design abilities and a practical appreciation of the product development process through appropriate group individual activities; and the ability to coordinate multi-disciplinary projects, to make trade-offs among the available technology options with respect to cost, schedule, and risk, and to design and integrate motion control systems emphasizing motor and mechanism sub-systems; X
2 The program will enable students to develop: Work as an effective member of a design team; Communicate technical results to specialists and non-specialists. X
PERSONAL & OCCUPATIONAL COMPETENCES IN TERMS OF EACH OF THE FOLLOWING GROUPS
Autonomy & Responsibility
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 To produce mechatronic engineers who are capable of integrating the diverse disciplines of mechanical, electronic and computer engineering with a view to: 1.Design and develop high value-added consumer products with microprocessor control. 2.Design, implement and manage industrial automation machines, systems and facilities. X
Learning to Learn
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 Awareness of the necessity of lifelong learning; ability to reach information, follow the latest developments in science and technology; ability to ensure self-renewal perpetually. X
Communication & Social
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 Ability to communicate efficiently both in oral and written ways in Turkish; knowledge of at least one foreign language; ability to effectively prepare reports and understand written reports, prepare design and production reports, effective presentation; giving and receiving clear and understandable instructions. X
Occupational and/or Vocational
No PROGRAMME LEARNING OUTCOMES LEVEL OF CONTRIBUTION*
0 1 2 3 4 5
1 Acting in line with ethical principles, sense of professional and ethical responsibility; knowledge on the standards of engineering applications. X
*Level of Contribution (0-5): Empty-Null (0), 1- Very Low, 2- Low, 3- Medium, 4- High, 5- Very High

No
Key Learning Outcomes of the Course Unit
On successful completion of this course unit, students/learners will or will be able to:
PROGRAMME LEARNING OUTCOMES
1 to make the students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI).1 (4), 3 (3), 4 (4), 5 (3), 7 (4), 8 (3), 9 (4), 10 (4)
2 bottom-up approaches to solutions of (hard) problems based on various heuristics (soft computing), rather than exact approaches of traditional artificial intelligence based on logic (hard computing).1 (3), 3 (3), 4 (4), 5 (4), 7 (4), 8 (4), 9 (3), 10 (3)
3 The course goal is to make students familiar with basic principles of various computational methods of data processing that can commonly be called computational intelligence (CI).

Assessment
Assessment & Grading of In-Term Activities Number of
Activities
Degree of Contribution (%)
Mid-Term Exam 0 -
Computer Based Presentation 0 -
Short Exam 0 -
Presentation of Report 0 -
Homework Assessment 0 -
Oral Exam 0 -
Presentation of Thesis 0 -
Presentation of Document 0 -
Expert Assessment 0 -
Board Exam 0 -
Practice Exam 0 -
Year-End Final Exam 0 -
Internship Exam 0 -
TOTAL 0 %100
Contribution of In-Term Assessments to Overall Grade 0 %50
Contribution of Final Exam to Overall Grade 1 %50
TOTAL 1 %100


WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites Learning Activities
(# of week)
Duration
(hours, h)
Workload (h)
Lecture & In-Class Activities 14 3 42
Preliminary & Further Study 14 3 42
Land Surveying 0 0 0
Group Work 0 0 0
Laboratory 0 0 0
Reading 2 6 12
Assignment (Homework) 2 6 12
Project Work 2 6 12
Seminar 0 0 0
Internship 0 0 0
Technical Visit 0 0 0
Web Based Learning 0 0 0
Implementation/Application/Practice 0 0 0
Practice at a workplace 0 0 0
Occupational Activity 0 0 0
Social Activity 0 0 0
Thesis Work 0 0 0
Field Study 0 0 0
Report Writing 0 0 0
Total Workload for Learning & Teaching Activities - - 120
Workload for Assessment Activities
Type of the Assessment Activites # of Assessment Activities
Duration
(hours, h)
Workload (h)
Final Exam 1 3 3
Preparation for the Final Exam 1 3 3
Mid-Term Exam 0 0 0
Preparation for the Mid-Term Exam 0 0 0
Short Exam 0 0 0
Preparation for the Short Exam 0 0 0
Total Workload for Assessment Activities - - 6
Total Workload of the Course Unit - - 126
Workload (h) / 25.5 4.9
ECTS Credits allocated for the Course Unit 5.0

EBS : Kıbrıs İlim Üniversitesi Eğitim Öğretim Bilgi Sistemi Kıbrıs İlim Üniversitesi AKTS Bilgi Paketi AKTS Bilgi Paketi ECTS Information Package Avrupa Kredi Transfer Sistemi (AKTS/ECTS), Avrupa Yükseköğretim Alanı (Bologna Süreci) hedeflerini destekleyen iş yükü ve öğrenme çıktılarına dayalı öğrenci/öğrenme merkezli öğretme ve öğrenme yaklaşımı çerçevesinde yükseköğretimde uluslarası saydamlığı arttırmak ve öğrenci hareketliliği ile öğrencilerin yurtdışında gördükleri öğrenimleri kendi ülkelerinde tanınmasını kolaylaştırmak amacıyla Avrupa Komisyonu tarafından 1989 yılında Erasmus Programı (günümüzde Yaşam Boyu Öğrenme Programı) kapsamında geliştirilmiş ve Avrupa ülkeleri tarafından yaygın olarak kabul görmüş bir kredi sistemidir. AKTS, aynı zamanda, yükseköğretim kurumlarına, öğretim programları ve ders içeriklerinin iş yüküne bağlı olarak kolay anlaşılabilir bir yapıda tasarlanması, uygulanması, gözden geçirilmesi, iyileştirilmesi ve bu sayede yükseköğretim programlarının kalitesinin geliştirilmesine ve kalite güvencesine önemli katkı sağlayan bir sistematik yaklaşım sunmaktadır. ETIS : İstanbul Aydın University Education & Training System Cyprus Science University ECTS Information Package ECTS Information Package European Credit Transfer and Accumulation System (ECTS) which was introduced by the European Council in 1989, within the framework of Erasmus, now part of the Life Long Learning Programme, is a student-centered credit system based on the student workload required to achieve the objectives of a programme specified in terms of learning outcomes and competences to be acquired. The implementation of ECTS has, since its introduction, has been found wide acceptance in the higher education systems across the European Countries and become a credit system and an indispensable tool supporting major aims of the Bologna Process and, thus, of European Higher Education Area as it makes teaching and learning in higher education more transparent across Europe and facilitates the recognition of all studies. The system allows for the transfer of learning experiences between different institutions, greater student mobility and more flexible routes to gain degrees. It also offers a systematic approach to curriculum design as well as quality assessment and improvement and, thus, quality assurance.