Faculty of Engineering

Artificial Intelligence Engineering

Duration 4 Years
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About the Program

This program aims to train individuals who can develop artificial intelligence techniques and tools, are capable of analyzing and producing solutions for problems that are required for data collection and interpretation. It is also aimed to train students with the ability to select, use and evaluate the analysis and development stages of software systems, using current technologies in the information sector and equip students with skills in software analysis and development.
In this regard, it is aimed to enable Artificial Intelligence Engineering students to analyze data, be able to detect related problems and find appropriate solutions and implement theseis solutions by using the possibilities offered by artificial intelligence technologies. It aims to enable students by gaining knowledge, by working on the effective use of artificial intelligence engineering.
It is also aimed to train engineers who can always renew themselves and contribute to the field of artificial intelligence engineering and have developed a research culture about the rapidly developing software systems.

Education Opportunities

The Artificial Intelligence Engineering Program was established to enable students to gain interdisciplinary competence through a curriculum enriched by computer engineering, information systems engineering, and software engineering program courses.
By attending an internship during the last year of the Artificial Intelligence Engineering Program, students will be able to start their career life one step ahead with the practical experience they will gain. To reinforce the theoretical knowledge they have obtained, students are provided with a wide range of laboratories at CIU, which allow them to experience software or hardware development processes, involving artificial intelligence.

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Career Areas

Students who will graduate from the Artificial Intelligence Engineering Program, will take the title of an “Artificial Intelligence Engineer” and will be able to be employed at all areas in the software and robotics sector.
Intelligence methods are needed in computer software and robotics practices used in many industries today. Students will be competent enough to do sectoral software development work mainly in engineering, banking and finance, education, medicine, and public areas. They will also be able to continue their academic careers by doing a Master's or a Doctorate Degree.

Contact

Faculty of Engineering
Science and Technology Center, ST 226
Tel: +90 392 671 1111 Extension: 2401
Faculty E-mail: secretary-fe@ciu.edu.tr
Head of Department: Asst. Prof. Dr. Devrim Seral
Head of Department E-mail: dseral@ciu.edu.tr

Compulsory modules

First Semester
INTRODUCTION TO ARTIFICIAL INTELIGENCE ENGINEERING

Course code

AIEN100

Credit

0

Theoretical

1

Practical

0

Ects

0
This course presents the basics of the Artificial Intelligence Engineering program, as well as Computer Science. The fundamentals of software and data science in a computer system are discussed. Other topics include representation of information, logic design, fundamentals of software life cycles, programming languages, data analysis and machine learning as well as robotics and its business applications. Also, ethical and social responsibilities of engineers are studied. Departmental facilities and the software’s used in the university like registration software (SIS) or course management site (moodle) are also introduced to students. Besides, the campus life and the curriculum of the department are in the scope of the course. Moreover, academic life and its procedures like grade average calculations, letter grades and other academic issues are discussed.
INTRODUCTION TO COMPUTING

Course code

CMPE101

Credit

3

Theoretical

2

Practical

2

Ects

5
This course presents the basics of computer systems. The course is structured in two parts; including a short history of computers, the first part of this course presents the history, basic concepts and terminology of information technology, basic hardware and software components of a computer system, and integration of computer system components. Besides the terminologies and abbreviations, the students learn about the hardware setup of a personal computer and the relations between the processor, memory and secondary devices. The laboratory part includes basic computer usage and office programs (MS Word, Excel). In the second part, basics of problem solving approaches, components and construction of computer programs, flow-charting, and modular programming issues are discussed. Basics of C programming language are covered in classroom.
READING AND WRITING SKILLS-I

Course code

ENGL141

Credit

3

Theoretical

2

Practical

2

Ects

4
This course aims to develop students' listening, speaking, reading - writing and study skills. The course provides students with the opportunity to develop their communication skills through controlled activities and to equip students with the basic study skills necessary to follow the curriculum of English. This course also provides students with the opportunity to process the newly acquired knowledge and to develop their ability to ask questions about how to apply the new knowledge to new situations and ask them to think critically. In addition, this course will enable students to learn about the different strategies required to review the various reading pieces, such as finding the main idea and distinguishing the details from the main idea.
CALCULUS-I

Course code

MATH101

Credit

4

Theoretical

3

Practical

2

Ects

6
Calculus-I provides the methods of differential and integral calculus with applications in geometry, physics and engineering. Students in this course will learn how to use mathematical language needed for applying the concepts of calculus to numerous applications in science and engineering such as identifying types of functions, graph of functions, evaluating limit of functions, limit of elementary functions (polynomial, trigonometric, logarithmic, exponential,…), methods to solve the undefined limits (L’Hopitals Rule), continuous functions, evaluate derivative of functions, definition of derivative, derivative of elementary functions, derivative of product of two functions and division of functions, applications of derivative, evaluate integrals of functions, definition of the integral, integral of elementary functions, substitution method, integration by parts, integral of rational functions, application of the integral (finding the area) .
LINEAR ALGEBRA

Course code

MATH121

Credit

2

Theoretical

2

Practical

0

Ects

4
The aim of this course is to introduce the basic operations in linear algebra and applications in engineering problems; matrices, matrix properties and matrix operations: Addition, scalar multiplication, multiplication, transpose, solution of system of linear equations: Elimination method, Gauss Jordan forms, inverse method to solve linear systems, row reduced echelon forms, Gaussian elimination method, inverse and determinants: solving linear equations with determinant (Cramer's rule), use one row to evaluate determinant, minor, cofactor, adjoint matrix, identity matrix, square matrix of the matrices. Real vector spaces, vectors and their properties and applications in engineering: Addition, subtractions, dot product, scalar multiplication, cross product, basis, dimensions and subspaces.
GENERAL PHYSICS-I

Course code

PHYS101

Credit

4

Theoretical

3

Practical

2

Ects

6
The aim of the course is to provide the basic information in order to help the students to understand the possible complicated problems in engineering. In this regard, the basic principles and methods of solving the problems in physics are thought. The course provides a basic grounding in elementary physics including mechanics. The basic subjects of the course are: Units and dimensions, Uniformly accelerated motion in one dimension, Freefall, Vector mathematics, Two dimensional motion, Newton’s laws of motion, Applications of Newton’s laws, Free body diagrams, Circular motion, Work and energy, Conservation of energy, Momentum, impulse, and collisions, Rotational kinematics, Torque, Static equilibrium. For completeness, the students are supposed to do 6 experiments related to the subjects of the course.
TURKISH LANGUAGE

Course code

TREG100

Credit

0

Theoretical

2

Practical

0

Ects

2
This course examines basic areas of language and expression. In the first half of the course, the theoretical approach to language is formed and the spelling rules of the Turkish language are studied. In the latter part of the course, language and narrative errors are studied together with editing. In the second half of the course, formal writing, curriculum vitae, petition, evaluation of the columns in terms of language and style, types of written expression and practice; Turkish production and application of shooting attachments; Turkish grammar structure; It is aimed to teaching subjects like phonetics of Turkish to students.
TURKISH

Course code

TURK100

Credit

0

Theoretical

2

Practical

0

Ects

2
This course provides an orientation to modern Turkish language for foreign students who wish to communicate in this language for their needs. It mainly focuses on the differences between Turkish and English Alphabets, especially the sounds and the letters which are not included in the English alphabet (i.e. Turkish letters ç-ğ-i-ö-ş-ü). In addition, basic grammar and sentence structure forms in Turkish are practised. The required grammar and vocabulary will also be developed through their adaptation to daily situations in contexts such as introducing yourselves, greeting, talking about the things they possess by using possessive adjectives, forming positive, negative and question sentences by using present simple, telling the time, talking about their own timetables, using demonstrative pronouns when describing the place of objects and becoming familiar with vocabulary related to family members.
Second Semester
INTRODUCTION TO PROGRAMMING

Course code

CMPE112

Credit

4

Theoretical

3

Practical

2

Ects

6
The course will introduce basic and fundamental programming constructs and techniques through using the C++ programming language in order to generate algorithmic solutions to problems. Upon completion of the course, students will learn an introduction to algorithms, solving problems by flowcharts and pseudo codes, header files, data types, arithmetic & logic operators, control statements (if, if/else, switch-case) and use them as inner statements, loop statements (while, do/while, for), functions, standard functions of programming language, random number generation and their area of use, user-defined functions, global and local variables, recursion, arrays, searching algorithms on arrays, sorting algorithms on arrays, pointers, pointer operators, using pointers with arrays and functions. In the laboratory hours, students are supposed to write full programs or modify existing programs for other solutions.
READING AND WRITING SKILLS-II

Course code

ENGL142

Credit

3

Theoretical

2

Practical

2

Ects

4
This course is the continuation of ENG 101. The course aims to improve students' listening, speaking, reading, writing and working skills. In the course, students are guided in writing compare and contrast essays using Venn diagram. In addition, the aim of the course is to learn the necessary conjunctions for composition writing. In addition, the students will be able to write a four-part critical composition by learning the difference between ideas and factual real sentences and how to write the opposing opinion and sentences used to refute it. Thus, the students will be able to distinguish between the compare and contrast essay and discursive essay. Students will also be able to make presentations by using presentation techniques. In addition, this course aims to summarize the reading pieces of the students and to use the strategies of reading and to draw conclusions and meanings using their reading skills.
HISTORY OF CIVILIZATION

Course code

HIST100

Credit

0

Theoretical

2

Practical

0

Ects

2
The aim of this course is to outline the development of civilizations in the course of history. It firstly focuses on the concepts such as “Civilization”, “Prehistoric”, and “Historic” and on the factors forcing the emergence of the first civilizations. As well as examining the prehistoric periods and their characteristics in the course of human life since the first appearance of human beings on earth, the course mainly focuses on the early civilizations, namely the Mesopotamian, Egyptian, Aegean, Classical Greek, Hellenistic, Indian, Chinese and Roman Civilizations. Political, social, economical, cultural, intellectual, philosophical and scientific aspects in these entities are also examined in this course.
CALCULUS-II

Course code

MATH102

Credit

4

Theoretical

3

Practical

2

Ects

6
This course provides the methods of differential and integral calculus with applications in geometry, physics and engineering. Topics included are as follows: Sequences and infinite series, properties of sequences, test for convergence, tests for series with both positive and non-positive series, absolutely convergence and conditionally convergence . Power series, Taylor and Maclaurin series, the radius of convergence. Parametric equations and Polar coordinates, the graph of polar equations, the area in polar coordinates, arc length, speed on a curve and derivative of polar equations. Vectors and vector-valued functions, dot product and cross product of two vectors. Lines and Planes. Functions of several variables, their domain, limit and partial derivatives and definite integral of a function over a region.
DISCRETE MATHEMATICS

Course code

MATH122

Credit

3

Theoretical

3

Practical

1

Ects

5
The objective of the course is to introduce the students fundamental principles: logic and Boolean algebra, set theory, relations( Partial ordering, Total ordering and Hasse diagrams, Equivalence relations and equivalence classes), functions(one-to-one, onto, identity, inverse and composition of functions), inductive proofs and recurrence relations, counting techniques(multiplication and addition rules, permutations, combinations, unordered samples with repetitions, principle of inclusion and exclusion, pigeonhole principle) and introduction to graph theory(basic terminology like vertex, edge, degree of a vertex in directed and undirected graphs, Eulerian and Hamiltonian graphs, trees and spanning trees, minimal spanning trees, Prim’s Algorithm, Kruskal Algorithms, Shortest Path Problems, Dijkstra’s Algorithm).
GENERAL PHYSICS-II

Course code

PHYS102

Credit

4

Theoretical

3

Practical

2

Ects

6
This course provides the basic information to help the students to understand the possible complicated problems in engineering. The subjects of the course are mostly Electricity and Magnetism. The basic subjects of the course are Properties of electric charges, Coulomb’s law, and Electric field of a continuous charge distribution, Gauss’s law and electric flux. Application of Gauss’s law to charged insulators, Obtaining the value of the electric field from the electric potential, Electric potential and the potential energy due to point charges, Electric potential due to continuous charge distributions, Electric current, Resistance and Ohm’s law, Electromotive force, Resistors in series and in parallel. Kirchhoff’s rules. For completeness, the students are supposed to do 6 experiments all are related to the subjects of the course.
MODERN TURKISH HISTORY

Course code

TARH100

Credit

0

Theoretical

2

Practical

0

Ects

2
In this course, Ottoman state and society, factors causing the collapse of the state; Ottoman modernization; Tripoli and Balkan Wars, World War I, Mudros Armistice and Sevres Agreement; parties and associations, the national resistance movement led by Mustafa Kemal, the Havza and Amasya Circulars, the Congresses, the National Pact, the Turkish Grand National Assembly; the rebellions, the regular army and the War of Independence; the Mudanya Armistice, the Lausanne Peace Treaty; Revolution in the political field, secularization of the state and society, abolition of the sultanate, declaration of the republic, abolition of the caliphate; 1921 and 1924 constitutions, constitutional changes; Sheikh Said Rebellion; Multi-party experience, secularization and modernization in law, nationalization and secularization in education, Kemalizm and 6 principles, Turkish foreign policy(1923-1938) are covered.
Third Semester
PRINCIPLES OF ARTIFICIAL INTELLIGENCE

Course code

AIEN201

Credit

3

Theoretical

3

Practical

0

Ects

0
This course aims to present the main concepts and techniques used in Artificial Intelligence (AI) and introduce a range of real-world AI applications. The students will acquire knowledge about the history and the foundations of AI, and the basis required for developing autonomous intelligent agents. By the end of the course students are expected to have the fundamental knowledge on principles of artificial intelligence, develop problem solving skills on various artificial intelligence problems and implement related real world applications. In addition to the topics stated above, the AI students are also expected to gain general knowledge about the development of basic autonomous systems.
DIGITAL LOGIC DESIGN

Course code

CMPE221

Credit

4

Theoretical

3

Practical

2

Ects

5
This course presents the basic tools for the design and analysis of digital circuits and provides methods and procedures suitable for a variety of digital design applications in computers, control systems, data communications, etc. The course introduces data representation in binary systems, complements, Boolean algebra, logic gates, truth tables, logic circuits, timing diagrams, De Morgan's law, algebraic manipulation, minterms and maxterms, Sum of Products (SOP) and Product of Sums (POS) forms, Boolean function simplification tools and Karnough Map method, NAND and NOR implementations, don't care conditions, combinational circuit design and analysis procedures, and design of Adders, Subtracters and Code Converters.
ALGORITHMS AND PROGRAMMING

Course code

CMPE223

Credit

4

Theoretical

3

Practical

2

Ects

6
The course mainly focuses on software implementations in C Programming Language. Firstly, basic concepts of algorithms are discussed and then structures of programming are studied. Then, arrays and searching and sorting algorithms on arrays are studied. Fundamentals of basic data structures, which are arrays, structures and unions are discussed together with bitwise operations and enumerations in C. Pointers, functions and file processing are studied in the second part of the course, after midterm examination. Case studies related to searching and sorting algorithms are also studied. Functions, characters and strings are studied as last topics of algorithm developments and course is finalized with complexity analysis of algorithms.
DIFFERENTIAL EQUATIONS

Course code

MATH203

Credit

3

Theoretical

3

Practical

1

Ects

6
In this course, the ordinary differential equations and their applications will be considered. The course will demonstrate the usefulness of ordinary differential equations for modelling physical and engineering problems. Complementary mathematical approaches for their solution will be presented, including analytical methods. The basic content of the course includes first order ordinary differential equations and their types of exact, separable, Bernoulli, first order, homogeneous ordinary differential equations, linear independence of the solutions, higher order ordinary differential equations and their solutions. The undetermined coefficient methods, the variation of the parameter method, Cauchy-Euler equations. The definition of the Laplace transform and some important applications of the Laplace transform will be included in this lecture.
INTRODUCTION TO PROBABILITY AND STATISTICS

Course code

MATH205

Credit

4

Theoretical

4

Practical

1

Ects

6
The objective of this course is to introduce basic probability and statistics concepts. The focus of this course is on both applications and theory. Topics include: introduction to random variables, simple data analysis and descriptive statistics, frequency distribution, cumulative distribution, sample space, events, counting sample points (basic combinatorics), probability of an event, probability axioms, laws of probability, conditional probability, Bayes’ rule, discrete and continuous random variables, probability distributions, cumulative probability distributions, discrete and continuous probability distributions, discrete uniform, Binomial, Geometric, Hypergeometric, Poisson, Continuous uniform, Normal Disributions, Gamma and Exponential distribution, jointly distributed random variables, expectation and covariance of discrete and continuous random variables, random sampling, sampling distributions, distribution of Sample Mean, Central Limit Theorem(CLT).
Fourth Semester
INTRODUCTION TO DATA SCIENCE

Course code

AIEN202

Credit

4

Theoretical

3

Practical

2

Ects

0
This course is designed to provide students with a general understanding of the basic concepts and core techniques of data science. Students explore the computational methods and statistical tools to analyze and make sense of data. Upon completing the course, students will be able to: utilize tools to collect, clean and visualize data; employ data management techniques to effectively access, manipulate and store data; apply statistical methods to make predictions based on data; communicate their results through descriptive summaries and visualizations. Topics will include: Data collection and data management, visualization and basic statistics, hypothesis testing and causality, similarity, neighbors and clusters, large scale data analysis, collaborative filtering.
VISUAL PROGRAMMING

Course code

CMPE214

Credit

3

Theoretical

3

Practical

1

Ects

6
This course is an introductory programming course for visual programming. Event-driven, visual and structured programming concepts will be presented. Initially, the emphasis will be on fundamentals of visual programming and basic controls. Then, advanced controls, file and database management features will be presented. Programming projects will involve common problems that require data entry, display of calculated results, conditional testing, arithmetic operations, array processing, searching, sorting, reading and writing files, and operations on databases.
DATA STRUCTURES AND DATA ORGANIZATION

Course code

CMPE242

Credit

4

Theoretical

3

Practical

2

Ects

7
The objective of this course is to provide the basics of data structures and data organization. The course will introduce C/C++ and algorithms for the implementation of data structures which are stack, queue, linked list, tree. Also, the applications of data structures covering stack applications which are paranthesis checker, infix to postfix and prefix conversions, recursion, dynamic stack and queue, tree traversals. Linked lists with their types and implementations are also studied in details. Theoretical aspects of most widely used data structures will be covered during the lectures. Programming assignments and labworks cover the C/C++ implementations of applications of data structures that are discussed in the lectures.
ENGINEERING ECONOMY

Course code

INDE232

Credit

3

Theoretical

3

Practical

0

Ects

4
The purpose of this course is to provide an introductory basis for economic analysis in decision making process in engineering design, manufacturing equipment and industrial projects. This course aims to supplement engineering students with the knowledge and capability to perform financial analysis especially in the area of capital investment. It emphasizes the systematic evaluation of the costs and benefits associated with proposed technical projects. The student will be exposed to the concepts of the “time value of money” and the methods of discounted cash flow. Students are prepared to make decisions regarding money as capital within a technological or engineering environment. Assignments and homework help and guide the students to apply the knowledge acquired during the course.
MATHEMATICAL METHODS FOR ENGINEERS

Course code

MATH202

Credit

4

Theoretical

3

Practical

2

Ects

6
Aim of this course is to give complex analyse and fundamental methods to solve numerical problems in mathematics, computer science, physical sciences and engineering. Topics included are as follows: Definitions: Error types, Taylor series and truncation error and rounding numbers. Numerical solution of nonlinear equations; Bracketing methods, Bisection and False position, Iterative methods: Fixed point and Newton method. Numerical methods for solution of linear systems, Iterative methods and LU decomposition methods. Interpolation and polynomial approximation, Lagrange polynomials, Least square lines, curve fitting and spline functions (linear and quadratic). Evaluate derivatives by numerical analysis, numerical differentiation, finite difference formulas. Evaluate integrals by numerical analysis, numerical integration, Simpson's rules and Trapezoidal rules. Complex numbers, complex functions, derivative and integral of complex functions.
Fifth Semester
PROGRAMMING FOR ARTIFICIAL INTELLIGENCE

Course code

AIEN301

Credit

3

Theoretical

3

Practical

1

Ects

0
The aim of this course is to explore the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By the end of the course, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
OBJECT ORIENTED PROGRAMMING

Course code

CMPE313

Credit

4

Theoretical

3

Practical

2

Ects

7
The objective of course is to identify the classes (including attributes, behaviors and methods), object and their relationships by reading the problem description, draw objects diagrams by looking to the defined problem description, implement Java class by looking at the given UML Class Diagram, use existing industry standard coding and formatting conventions, event mechanisms in Java, construct a GUI based applications using Java and Eclipse and debug those applications, technically identify the differences between classes, objects, inheritances, polymorphism, interfaces, aggregation, composition and abstract class. In addition, the issues of code re-use and software quality will be discussed and the use of inheritance will be shown through for code re-use.
DATABASE MANAGEMENT SYSTEMS AND PROGRAMMING-I

Course code

CMPE343

Credit

4

Theoretical

3

Practical

2

Ects

6
At the end of this course, students are expected to have experience and knowledge on databases, database design and SQL. Introduction to DBMS (Definition, characteristics, levels of abstraction, advantages, query types), Relational database (relational model, database design), Relational Algebra, SQL, Data Manipulation Language (DML), nested queries, sub-queries, joins, grouping, row functions, aggregate functions, Data Definition Languages (DDL) with constraints like primary key, foreign key and case constraints will be covered. Also, database user management and user rights will be explained.
OPERATING SYSTEMS

Course code

CMPE351

Credit

4

Theoretical

3

Practical

2

Ects

6
This course examines basic issues in operating system design and implementation. The course will start with a brief historical perspective of the evolution of operating systems over the last fifty years, and then cover the major components of most operating systems. This discussion will cover the trade-offs that can be made between performance and functionality during the design and implementation of an operating system. Particular emphasis will be given to these major OS subsystems: Process management (processes, threads, CPU scheduling, synchronization, and deadlock), memory management (segmentation, paging, swapping), file systems, and networking/distributed systems. Also basic Unix programming skills will be given during lab hours.
SIGNALS & SYSTEMS

Course code

EELE321

Credit

4

Theoretical

4

Practical

1

Ects

7
Classification of Signals and Basic Signal Properties. Time Domain Models of Linear Time Invariant (LTI) Systems: Continuous time systems. Causal LTI systems described by differential equations. System block diagrams. The solutions of differential equations. The unit impulse response and convolution integral. State variable analysis of LTI systems. Discrete time systems. The unit sample response and discrete convolution. Fourier series and Fourier transform representation of continuous-time and discrete- time periodic signals. Time and frequency characterization of signals and systems. Z-transform and inverse z-transform. Region of convergence of the z-transform. z-domain analysis of discrete LTI systems. LTI Systems With Random Inputs. Definition of Random variables, stochastic process, first and second order statistics, moment, correlation and co-variance, stationary process, ergodicity. System resonse.
Sixth Semester
MACHINE LEARNING

Course code

AIEN302

Credit

4

Theoretical

3

Practical

2

Ects

0
The subject matter of this undergraduate-level introductory course is to provide students a broad overview of many concepts and algorithms in Machine Learning (ML) and equip students with the skills to apply these concepts to real world problems. After completing the course, the students, learn about the basic concepts in main machine learning. Topics will include Nearest Neighbor Classifier, Linear Regression, Least Squares, Learning Theory, Statistical Estimation: MLE, MAP, Naive Bayes Classifier, Linear Classification Models: Logistic Regression, Linear Discriminant Functions, Support Vector Machines, Decision Tree Learning, Ensemble Methods: Bagging, Boosting, Clustering, Ethics in Machine Learning, Feature Engineering: Extraction and Selection.
NEUROBIOLOGY

Course code

AIEN304

Credit

3

Theoretical

3

Practical

0

Ects

0
The main objective of the course is to introduce main concepts of neurobiology. This course will emphasize basic neural circuits, initiation and propagation of nerve signals, architecture and organization of basic central and peripheral nervous systems, saltatory and passive conduction of nerve signals. Upon completing the course, the students will learn about frequency and amplitude coding of nerve signals, Nernst and Goldman equations, time and space in signal propagation, resting membrane potential of neurons, ionic conductance, the Hodgkin and Huxley model of the action potential, transient inward current and delayed outward current. Topics of the course will also include, derivation of cable model, summation of signals, cellular ionic mechanisms including ion channels and transporters and post-synaptic potential.
SIGNAL AND IMAGE PROCESSING

Course code

CMPE326

Credit

3

Theoretical

3

Practical

1

Ects

5
Signal and Image Processing course is organised to introduce the fundamentals of digital signal and image processing techniques. The emphasis will be on analysis tools, the design of digital filters, and on the computation of the Discrete Fourier Transform (DFT). The course is designed to give all the fundamental concepts in digital image processing with emphasis in spatial filtering, frequency domain filtering, image enhancement, image restoration, compression, segmentation. Morphological image processing and the introduction to object recognition are the last topics of the course. Included in these topics, the interpolation techniques, frequency domain filtering and image averaging methods for noise removal are important topics covered. The studied methods are experimented using simulator program.
FUNDAMENTALS OF COMPUTER NETWORKS

Course code

CMPE332

Credit

4

Theoretical

3

Practical

2

Ects

7
This is an introductory course in computer networks. It first introduces uses of Computer Networks in Business, Home and Mobile environment. Next discusses types of computer network range from personal area network to Internet. It then studies the implementation principles and design issues at each layer of network models. Lecture topics include: OSI and TCP/IP models, data transmission basics, data-link, application Layer protocols, guided and unguided transmission, satellite communication ( LEO, MEO, GEO) digital modulation and multiplexing, PSTN and Mobile telephone systems. Laboratory work focuses on building and studying a physical network using network devices, wired and wireless medium.
UNIVERSITY ELECTIVE

Course code

UNIEXX1

Credit

3

Theoretical

3

Practical

0

Ects

4
UNIVERSITY ELECTIVE
Seventh Semester
SUMMER TRAINING

Course code

AIEN300

Credit

0

Theoretical

0

Practical

0

Ects

0
The summer internship includes a minimum of six weeks of study period during which students are required to work in a company operating in the fields of information technologies or software engineering. During this period, students are expected to work on software or hardware parts in an active project and gain work experience. In order to attend the summer internship, students are required to be successful or enrolled in at least six third grade courses in total. Any student who meets these conditions may attend a summer internship. At least one relevant engineer is required in the place of internship. The students who complete the summer internship are evaluated with the internship report they complete and the internship book they record daily.
FUNDAMENTALS OF NEURAL NETWORKS

Course code

AIEN421

Credit

3

Theoretical

3

Practical

0

Ects

0
The neural networks course represents the basic neural network architectures and learning algorithms which are inspired from the human brain. Neurocomputing stands as a sub-topic of artificial intelligence together with evolutionary computing. Within the scope of the course, perceptrons and perceptron learning algorithm are introduced. The architectures include Multilayer Perceptrons, Hopfield Model and Self Organized Maps covering Mallberg’s and Kohonen’s models. Learning algorithms will cover the selected supervised and unsupervised learning algorithms including backpropagation, Hebbian learning, competitive learning and the selected clustering algorithms. Several pattern recognition and computer vision applications will be presented as case studies. The applications will be simulated on selected simulators.
AREA ELECTIVE

Course code

AIENXX2

Credit

3

Theoretical

3

Practical

0

Ects

0
AREA ELECTIVE
AREA ELECTIVE

Course code

AIENXX3

Credit

3

Theoretical

3

Practical

0

Ects

0
AREA ELECTIVE
ROBOTICS

Course code

EELE411

Credit

3

Theoretical

3

Practical

1

Ects

5
This course introduces fundamentals of robot control. Brief review about robots, hardware and robot problems will be explained to give a general idea about the use of robotics. Various types of basic sensors are also be discussed under the issue of robot hardware. Agent function design will be taught to gain robot control algorithm development and design. Robot control programming with mostly used controllers and related programming language concepts will also be covered to improve hardware programming skills of participants of this course. Lectures give the background to the extensive hands-on practical work using the laboratories A practical project will be performed to have an experience about to control a real robots with microcontroller.
PROJECT MANAGEMENT

Course code

ENGI401

Credit

3

Theoretical

3

Practical

0

Ects

4
This course is designed to focus on project management framework, project integration management, project scope management, project communication management and teamwork, health & safety, engineering ethics, environmental management, risk management and sustainability, entrepreneurship and feasibility report, legal aspects in project management. This course also prepares the senior students to select their capstone design projects and form teams. The students undertake literature review for their projects, prepare feasibility report, and a written/oral presentation at the end of the term.
Eighth Semester
NATURAL LANGUAGE PROCESSING

Course code

AIEN422

Credit

4

Theoretical

3

Practical

2

Ects

0
Natural Language Processing course covers topics to convert text data to processable information. Initial part of this course contains preliminary data processing to create feature matrix that will also cover stemming, lemmatization, part of speech tagging, bag of words, n-grams, stop words, normalization, idf, tf/idf. Distance metrics together with evaluation metrics (F-MEASUE, BLUE, ROUGE) will also revised in this course. Semantic feature extraction that covers named entity recognition, word sense disambiguation and dimensionality reduction with factorization methods will also be discussed. Application of variety number of machine learning techniques for text data is also covered in this course. Last section focuses on real world application like text summarization, author identification, text classification and categorization.
AREA ELECTIVE

Course code

AIENXX4

Credit

3

Theoretical

3

Practical

0

Ects

0
AREA ELECTIVE
AREA ELECTIVE

Course code

AIENXX5

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE
CAPSTONE PROJECT

Course code

ENGI402

Credit

4

Theoretical

2

Practical

4

Ects

8
This course is an interdisciplinary project based course involving engineering design, cost estimating, environmental impacts, project schedule and team work. Students are expected to work in pre-assigned team under the supervision of faculty on a predetermined project. Each team will submit a final report including drawing, specification, and cost estimate that completely describe their proposed design. Each team will make oral presentation defending their final design and project feasibility to peers and faculty members.
UNIVERSITY ELECTIVE

Course code

UNIEXX2

Credit

3

Theoretical

3

Practical

0

Ects

4
UNIVERSITY ELECTIVE

Optional modules

COMPUTER SIMULATION

Course code

CMPE485

Credit

3

Theoretical

3

Practical

0

Ects

TRNC citizens and TR citizen candidate students who have completed their entire high school education in TRNC. They are placed in undergraduate programs in line with their success in the CIU Student Placement and Scholarship Ranking Exam and the programs they prefer.

Students who are successful in the exam can register from the TRNC Marketing Office.

Applicants can directly apply online to our undergraduate programs by using the application portal. Please fill in your details correctly and upload all the required documents listed on the last page of the application form.

Required documents;

  • Completed application form,
  • Higher/Secondary Certificate or equivalents (e.g. O/A’Level, WAEC/NECO)
  • Evidence of English Language competence: TOEFL (65 IBT) or IELTS (5.5). Students without these documents will take the CIU English proficiency exam on campus following arrival,
  • Scanned copy of international passport/birth certificate,
  • Fully completed and signed CIU Rules and Regulations document (which can be downloaded during the online application).

Cyprus International University provides academic scholarships for its students as an incentive for success, with most students benefiting from 50%, 75% or 100% scholarships or discounted tuition fees. Click for more information.

  Non-Scholarship 50% Scholarship
Undergraduate Programs € 5.843,00 € 3.099,00

Click for more to learn about fees in line with the Tuition Fee Calculation system.