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Artificial Intelligence Engineering

SEMESTRE 1

MT111Calculus IPreReq.:-Credit:4
Real numbers, functions, and graphs; limits and continuity; the derivative and differentiation; extreme function values, techniques of graphing, and the exact differential.

PS111General Physics IPreReq.:-Credit:3
Introduces classical mechanics. Space and time: straight-line kinematics; motion in a plane; forces and equilibrium; experimental basis of Newton's laws; particle dynamics; universal gravitation; collisions and conservation laws; work and potential energy; vibrational motion; conservative forces; inertial forces and non-inertial frames; central force motions; rigid bodies and rotational dynamics.

CH101General ChemistryPreReq.:-Credit:3
Matter and measurements; Atom, molecules and ions. Stochiometry, the mole, mass relations in chemistry reactions; gases, kinetic theory of gases; electronic structure and the Periodic Table, quantum numbers, energy levels and orbitals. Covalent bonding, thermo-chemistry, calorimetry, bond energy, firs law of thermodynamics, liquids and solids, molecular substances, phase diagrams, types of solutions, concentration units, acid-base model, water dissociation constant, pH and pOH; Alkanes and alkenes, aromatic hydrocarbonates and their derivatives, functional groups, synthetic organic polymers, nuclear reactions, nuclear stability and radioactivity, nuclear fission, nuclear fusion.

ENG101Introduction to ComputersPreReq.:-Credit:3
An introduction to basic aspects of computing, operating systems, computing environments, networks and tools. This course provides a background of tools using DOS and Windows environments for word processing, spreadsheets and databases.

AIE101Introduction to AIPreReq.:-Credit:3
Introduction to Artificial Intelligence provides a comprehensive survey of the fundamental concepts and techniques that enable computers to perform tasks typically requiring human intelligence. It serves as the gateway to advanced studies in autonomous systems, machine learning, and robotics. This course explores the transition from traditional programming to heuristic search and probabilistic reasoning. Students learn how to model "intelligent agents" that perceive their environment and take actions to maximize their chances of success. Primary Goal is to understand the core logic and algorithmic foundations of modern AI.

TURK001Turkish IPreReq.:-Credit:0
This course introduces students to the fundamental concepts of the Turkish language, with an emphasis on its historical development and structural features. It explores the relationships between language and human experience, society, culture, and thought, as well as the position of Turkish among world languages. Students are introduced to the distinctions between spoken and written language and develop awareness of correct spelling and punctuation rules. The course also emphasizes clear and effective expression in both written and oral communication, highlighting its importance in personal and social contexts. Through guided reading, writing, and basic research practices, students begin to develop essential academic communication skills.

TFL101Turkish as Foreign Lang. IPreReq.:-Credit:0
This course is designed for international students with little or no prior knowledge of Turkish. It introduces the basic structures of the Turkish language, focusing on essential grammar, vocabulary, pronunciation, and everyday expressions. Students develop fundamental skills in listening, speaking, reading, and writing through communicative and task-based activities. By the end of the course, learners will be able to introduce themselves, ask and answer simple questions, and engage in basic conversations related to daily life.

SEMESTRE 2

MT112Calculus IIPreReq.:MT111Credit:4
The definite integral and integration; computing areas; application of the definite integral; inverse functions, and exponential functions; and inverse trigonometric functions, and hyperbolic functions. Computing anti derivative, rational functions. (Prerequisite: MT111)

PS112General Physics IIPreReq.:PS111Credit:3
Introduction to electromagnetism and electrostatics: electric charge, Coulomb's Law, electric structure of matter, conductors and dielectrics. Gauss's Law, Concepts of electrostatic field and potential, electrostatic energy. Electric currents, magnetic fields and Ampere's law. Magnetic materials. Time-varying fields and Faraday's law of electromagnetic induction; magnetism and matter; basic electric circuits; AC circuits and resonance; Electromagnetic waves and Maxwell's equations. (Prerequisite: PS111)

MT104Linear AlgebraPreReq.:-Credit:3
This course deals with subjects such as system of linear equations, matrices, determinants, introduction to eigenvalues and eigenvectors, dot product, cross product, vector spaces and linear transformations.

ENG102Computer Programming IPreReq.:ENG101Credit:3
In this computer programming course, students learn how to solve problem using computers. The concept and notation of algorithms. Problem analysis, development of algorithms and their implementation in a procedure-oriented language. Topics include the integrated programming environment (editing, computing, debugging), data types, operators, input/output structured programming, program control, passing parameters and arrays.

MT106Discrete MathematicsPreReq.:-Credit:3
This course introduces discrete mathematical structures and formal reasoning techniques that form the foundation of modern computing, software engineering, and artificial intelligence. Emphasis is placed on problem modelling, logical reasoning, algorithmic thinking, and applications relevant to contemporary computer society.

TURK002Turkish IIPreReq.:-Credit:0
This course builds on the foundations established in TURK001, focusing on improving students’ written and analytical communication skills. It covers various types of written expression, sentence and paragraph structures, and forms of expression in Turkish. Students practice note-taking techniques and engage in activities designed to strengthen critical thinking and comprehension skills, particularly in paragraph development and text analysis. The course further develops students’ ability to interpret, evaluate, and produce coherent texts, while reinforcing the importance of accurate and effective language use in academic and everyday contexts.

TFL102Turkish as Foreign Lang. IIPreReq.:-Credit:0
This course builds on the foundations established in Turkish as a Foreign Language I. It aims to expand students’ vocabulary and deepen their understanding of grammatical structures while improving fluency and accuracy in communication. Emphasis is placed on developing all four language skills through interactive activities, short texts, and real-life scenarios. By the end of the course, students will be able to handle routine tasks, describe experiences, express preferences, and participate in simple conversations in familiar contexts.

SEMESTRE 3

CEN217Operating SystemsPreReq.:-Credit:4
This course introduces the fundamentals concepts and structure of modern operating systems (as an example, MS DOS, LINUX, and Windows). Topics include CPU, memory, file and device management, distributed systems and group communication. Processes and their communication, scheduling methods and algorithms are in the implementation focus. Distributed operating systems and their resources are considered. File-service system and remote access.

AIE201Fundamentals of AIPreReq.:-Credit:3
Fundamentals of Artificial Intelligence introduces the core principles and algorithms that allow computers to mimic human-like problem-solving. This course focuses on the "Classic" or "Symbolic" foundations of AI, providing the essential groundwork required to understand how modern intelligent systems are built. This course focuses on transitioning from simple code to heuristic search, logic-based reasoning, and optimization.

ENG203Computer Programming IIPreReq.:ENG102Credit:4
A continuation of the development of discipline in program design, implementation and in programming style. Topics include algorithms, recursion, and classical data structures. An additional language will be introduced.

ENG205Logic Circuit DesignPreReq.:-Credit:4
Number systems and codes, Binary, hexadecimal and octal systems, Boolean algebra and logic gates. Basic theorems, truth table, canonical and standard forms, Simplification of Boolean functions. Application of Boolean algebra to switching circuits, Minimisation of Boolean functions using algebraic: Karnaugh map, and tabular methods, Design of combinatorial circuits with MSI and LSI; decoders, encoders, multiplexers, and demultiplexers, programmable logic devices, flip-flops topics covered in this course.

AIE211Data Structures and AlgorithmsPreReq.:ENG102Credit:4
The objective of this course is to provide an introduction to data structures and algorithms. Topics include: control flow, loops, recursion; elementary data structures (lists, stacks, queues) and their implementation via array and pointers; advanced sorting algorithms, linear sorting algorithms, binary trees , general trees and heaps. Elementary graph algorithms. (Prerequisite: ENG102)

SEMESTRE 4

MT208Numerical AnalysisPreReq.:MT112Credit:3
Errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimum - maximum errors approximations; non-linear equations; eigenvalues and eigenvectors of matrices. (Prerequisite: MT112)

MT206Differential EquationsPreReq.:MT112Credit:4
Study of ordinary differential equations. Standard solution methods for first-order equation. Higher-order forced linear equations with constant coefficients. Complex numbers; Laplace transform. Matrix methods for first-order linear systems with constant coefficients. Series solutions to second-order equations. Fourier series solutions. (Prerequisite: MT112)

ENG206Digital SystemsPreReq.:ENG205Credit:4
Sequential logic circuits, state diagrams, applications of flip-flops, synchronous and asynchronous counters, shift registers, memories, interfacing, introduction to microprocessors and microcomputers, integrated circuit technologies. (Prerequisite: ENG205)

AIE212Introduction to Machine LearningPreReq.:-Credit:3
a foundational course that teaches how computers can learn from data without being explicitly programmed. It shifts the focus from writing rigid rules to building models that recognize patterns and make predictions based on examples. This course bridges the gap between computer science and statistics. It provides a broad introduction to the most common algorithms used in industry today. Primary Goal of the course is to understand how to select, build, and evaluate the right model for a given data problem.

AIE218Analysis of AlgorithmsPreReq.:ENG203Credit:4
This course introduces the students to the design of algorithms. The first part of the course presents recursion concepts and simple algorithms which rely on the recursion concept. The second part exposes some well known programming paradigms, such as brute force, divide and conquer, dynamic programming, greedy algorithms and applies them on several types of problems

SEMESTRE 5

CEN301MicroprocessorsPreReq.:ENG206Credit:4
Basic computer organisation and design. Instruction and their use. Instruction formats. Addressing techniques. Assembler language with examples from microprocessors. Detailed examination of addressing, instruction execution, data representation and program coding and debugging. Interrupt concept and usage. (Prerequisite: ENG206)

CEN305Object Oriented ProgrammingPreReq.:ENG203Credit:3
Building on a prior knowledge of program design and data structures, this course covers object oriented design, including classes, objects, inheritance, polymorphism, and information hiding. Student will apply techniques using a modern object oriented implementation language. (Departmental consent) (Prerequisite: ENG203)

AIE313Neural NetworksPreReq.:-Credit:3
This course introduces, in qualitative terms, what neural networks are, their properties and compositions. For the simplest class of neural networks, the least-mean-square algorithm (LMS) and the perceptron are examined. The multilayer perceptrons trained with the back-propagation algorithm and another class of layered neural networks, namely radial-basis function networks is introduced. The mathematical modelling of self-organizing maps and also the recurrent network architecture will be given.

AIE315Expert SystemsPreReq.:-Credit:3
This course explores how computer programs can emulate the decision-making ability of a human expert. It focuses on capturing specialized knowledge in a specific domain (such as medicine, engineering, or finance) and using logical rules to solve complex problems. This course provides a deep dive into the design and development of knowledge-based systems. Students transition from writing standard procedural code to creating systems that use reasoning to handle unstructured or semi-structured data. Primary Goal of the course is to understand how to transfer human expertise into a structured digital format.

MT307Probability TheoryPreReq.:-Credit:3
Theoretical definition of probability, various examples for probability, counting techniques, conditional probability, Bayes theorem, tree diagrams. Discrete and continuous probability distributions, mathematical expectation, standard normal distribution. Introduction to inferential statistics. Organising data, calculating mean, standard deviation, mode, median and range.

SEMESTRE 6

CEN302Structured Programming LanguagesPreReq.:-Credit:4
Introduction programming language design and implementation issues; language design and relation to compiler/interpreter design; block structured languages- block structure, scope, procedure mechanism, parameter passing, stack architecture. (Prerequisite: ENG102)

CEN306Database SystemsPreReq.:-Credit:4
This course introduces the basic principals of relational database systems, their structure and use. Topics covered include the use of entity relationship model in specifying a database; the relational model, and the translation of entity relationship; SQL and relational database design.

AIE322Deep LearningPreReq.:-Credit:3
Deep Learning is an advanced course that explores the design and implementation of artificial neural networks. It focuses on how multi-layered architectures can automatically learn complex features from massive datasets, such as images, text, and audio. This course transitions from "classical" machine learning to connectionist models inspired by the human brain. It covers the math and logic behind why deep architectures outperform traditional methods in high-dimensional tasks. Course mainly focuses on training Deep Neural Networks (DNNs) using backpropagation and gradient descent.

AIE324Introduction to Data MiningPreReq.:-Credit:3
Introduction to Data Mining teaches students how to discover hidden patterns, trends, and useful information within large-scale datasets. This course explores the intersection of statistics, machine learning, and database systems. It emphasizes the practical techniques used to extract non-trivial, previously unknown, and potentially useful information from massive data repositories. This course focuses on learning the specific algorithms used for classification, association, and outlier detection.

ENG304Engineering EconomyPreReq.:-Credit:3
Importance of engineering economy in industrial practice. Engineering economy related concepts, Present value of money, compound interest formulas, present worth methods, payback period, internal rate of return, capital cost, Benefit/cost rate, evaluation of alternative investment projects, mathematics of inflation, risk analysis.

SEMESTRE 7

AIE401Graduation Project IPreReq.:-Credit:3
The development of design skills and engineering judgement, based upon previous and current course and laboratory experience, is accomplished by participating in a design project. Projects are selected in areas of current interest in artificial intelligence engineering

AIE411Autonomous SystemsPreReq.:-Credit:3
Autonomous Systems is an interdisciplinary course focusing on the design and control of machines that can act independently in complex environments. It integrates robotics, control theory, and artificial intelligence to build systems capable of sensing, planning, and acting without human intervention. This course moves beyond static automation to explore systems that perceive their surroundings and make real-time decisions. Students study the "Perception-Planning-Action" loop that powers everything from self-driving cars to unmanned aerial vehicles. Primary Goal of the course is to develop the software architecture that allows a machine to navigate and complete tasks in uncertain environments.

ENG401Engineering EthicsPreReq.:-Credit:3
Engineering Ethics is a critical course that examines the moral responsibilities and professional obligations of engineers in society. It focuses on the ethical dilemmas that arise during the design, development, and implementation of technology, emphasizing the protection of public safety, health, and welfare. This course moves beyond technical calculations to explore the "human" impact of engineering. It provides students with a framework for identifying, analyzing, and resolving moral conflicts that occur in professional practice.

TELTechnical ElectiveCredit:3

TELTechnical ElectiveCredit:3

FELFree ElectiveCredit:3

NH001National History IPreReq.:-Credit:0
This course examines the historical background and development of the Turkish War of Independence and the transition from the late Ottoman Empire to the establishment of the Republic of Turkey. It introduces the concept of revolution (inkılap) and analyzes the political, social, and economic factors that led to the collapse of the Ottoman state. The course covers the national resistance movement, congresses, the formation and function of the Grand National Assembly, and the military and political stages of the independence struggle. It also addresses the proclamation of the Republic, the abolition of the Caliphate, and the early constitutional developments of the new state.

SEMESTRE 8

AIE402Graduation Project IIPreReq.:AIE401Credit:3
A continuation of AIE401 in which the design is implemented and demonstrated. This includes testing and demonstrating the performance and evaluation of results. (Prerequisite:AIE401)

CEN498Embedded SystemsPreReq.:-Credit:3
Learning the basics of designing, interfacing, configuring, and programming embedded systems. Gain competency in embedded systems field and in the implementation of learned techniques. Helping to prepare students for cutting edge careers in industry and research. Designing and programming a complete embedded system in intermediate level

CEN420Automata Theory & Formal LanguagesPreReq.:-Credit:3
Classification of automata and formal languages. Finite machines and regular events, context-free languages and machines with push-down memory, effectiveness, halting problem, insolvability, undecidability, and Turing machines.

TELTechnical ElectiveCredit:3

TELTechnical ElectiveCredit:3

FELFree ElectiveCredit:3

NH002National History IIPreReq.:-Credit:0
This course builds on NH001 by focusing on the reforms and principles that shaped the modernization of the Republic of Turkey. It examines the fundamental characteristics of the Turkish Revolution and the intellectual movements that influenced it. The course explores the establishment and development of key institutions, including the legal, educational, and economic systems, as well as reforms that transformed social life.

 TECHNICAL ELECTIVES



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