This is a course designed to introduce basic concepts in probability and statistics required in the modeling of uncertainty. Topics regarding probability include Bayes’ Theorem, discrete and continuous random variables and distribution functions (Bernoulli, Binomial, Hypergeometric, Poisson, normal, exponential, gamma, Weibull and multinomial distributions) whereas topics regarding statistics include Bayesian statistics, independent events; descriptive statistics of random variables, central limit theorem; joint distributions; sampling distributions; statistical estimation, confidence intervals; student-t, Chi-squared and F distributions; hypothesis testing; regression and correlation.

• Genetics and Bioengineering | Curriculum | Prerequisites / Conditions Graph
• Computer Science | Curriculum | Prerequisites / Conditions Graph

This course aims to familiarize students with the concepts of innovation and with the innovation ecosystem. The students will be provided with a review of innovation and management approaches and of innovative products and services in Turkey. They will be required to define a problem to be solved and formulate an innovative idea which provides a solution to the problem.

This course discusses issues in Future Engineering. Course aims to open a debate on the various subject topics and the related technologies that will be frequently on the engineering agenda in coming years. Each week, based on pioneering practices in the world and in Turkey supported by the presentation of an expert from industry or academia, it is targeted to provide a food of thought on the future of engineering as well as how novel engineering practices can design the future.

This course discusses ethical issues in the practice of engineering and science. Code of ethics for engineers, professional liability to clients, employers, and society, distinction of responsibility and accountability, legal obligations, and regulatory areas of concern to engineers, such as labor, safety and the environment, are among the topics examined. Case studies will be analyzed to understand concrete problems and their consequences.

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• Genetics and Bioengineering | Curriculum | Prerequisites / Conditions Graph
• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph
• Mechanical Engineering | Curriculum | Prerequisites / Conditions Graph
• Civil Engineering | Curriculum | Prerequisites / Conditions Graph
• Energy Systems Engineering | Curriculum | Prerequisites / Conditions Graph
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This course introduces the academic discipline and profession of Industrial Engineering (IE) to the students. Deductively, the course starts with systems thinking and goes on specifically trying to understand the design of industrial systems. Before any detailed work on industrial systems can be done, one needs to understand the design of such systems with a system review, paying special attention to the relationships between parts and management of design of industrial systems.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This compulsory summer practice consisting of 20 working days aims to introduce industrial engineering sophomore students to the work environment, particularly in production systems, and to provide field experience and basic skills in engineering practice.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

In this course, design, implementation, and analysis of algorithms are discussed at the introductory level. The course covers basic algorithm design techniques, analysis of the correctness and the efficiency of algorithms, and issues regarding implementation of algorithms.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This is a course designed to introduce basic concepts in probability required in the modeling of random processes and uncertainty. Topics include counting rules, probability concepts, Bayes’ Theorem, random variables, and probability distributions (Bernoulli, binomial, negative binomial, geometric, hypergeometric, Poisson, normal, exponential, gamma, Weibull).

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course aims to provide the concepts and principles of a variety of introductory statistical tools and techniques. The emphasis of this course is on the themes of summarizing data, confidence intervals, testing hypothesis, correlation and regression, and analysis of variance.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course covers fundamentals of optimization methods including the theory and application of linear programming problems with an emphasis on modeling concepts, linear programming models, simplex method, sensitivity analysis. Linear programming problems selected for this course are from diverse areas such as manufacturing, health care, transportation, etc.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course provides engineering students basic knowledge of micro and macro economics and also introduces the fundamental concepts of economic analysis for engineering and managerial decision making. In economics review, topics such as market economies, demand, supply, national income, employment, unemployment, inflation and economic growth are discussed. In economic analysis, topics such as time value of money, basic interest formulas, annual cost comparisons and present value analysis constitute the main content.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph
• Energy Systems Engineering | Curriculum | Prerequisites / Conditions Graph
• Civil Engineering | Curriculum | Prerequisites / Conditions Graph
• Electrical and Electronics Engineering | Curriculum | Prerequisites / Conditions Graph
• Mechatronics Engineering | Curriculum | Prerequisites / Conditions Graph
• Computer Engineering | Curriculum | Prerequisites / Conditions Graph
• Mechanical Engineering | Curriculum | Prerequisites / Conditions Graph

This compulsory summer practice consisting of 20 working days aims to introduce industrial engineering junior students to the work environment in production or service systems, and to provide field experience and basic skills in engineering practice.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course provides methods to plan, design and conduct experiments efficiently and effectively and analyze results to draw conclusion. The course starts with the introduction of basic concepts regarding design theory such as experiments, factors, randomization, and treatment. In order to analyze experimental data, Analysis of Variance (ANOVA) is presented. Different techniques and approaches are introduced for design of experiments such as factorial designs, fractional designs. Problems in the areas of production and service systems such as product and process design and development are addressed.

This course studies the principles and practice of the planning and designing of facility layout. The study covers design techniques for solving problems in plant layout, including topics such as site location, calculation of facility requirements, production activity, non-production activity, material handling, storage systems and group technology layout. Computer aided layout design techniques and evaluation of design software are also included.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course provides information on fundamentals of work methods, measurement and analysis and design of human work systems. Theory and application of work analysis and design as related to job operation, workplace layout, tools, equipment and services, and process design are discussed. Topics include operation analysis, manual work design, work environment design, time studies, charting techniques and schematic models, work samplings, predetermined time systems, and standard data.

The Ergonomics course is concerned with the achievement of optimal relationships between humans and their work environment. Topics include the capabilities and limitations of humans and machines, principles of symbolic and pictorial displays, static and dynamic forces on the human body, responses to environmental stress, injuries from poorly designed.

This course examines concepts, tools and methods of production planning and control. Topics included are forecasting methods, aggregate production planning, inventory management concepts, static lot sizing models (Economic Order Quantity, Economic Production Quantity, Quantity Discounts), dynamic lot sizing models (Heuristics and Wagner-Whitin algorithm), inventory review policies, Master Production Schedule (MPS), Material Requirements Planning (MRP) and capacity planning.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course examines the design and analysis of production systems. Topics included are push and pull production systems, Just-in-Time (JIT) and lean manufacturing, operations scheduling in flow shop and job shop environments, capacity planning, distribution planning, Enterprise Resource Planning (ERP) and integrated systems.

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The main subjects of the course are duality, transportation problems, assignment problems, network problems and integer programming problems.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

Stochastic processes, discrete and continuous time Markov chains, queuing theory and systems and renewal theory are the main subjects covered in this course.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

The topics covered in this course are basic principles of model building, and simulation tasks, such as input analysis, output analysis, verification and validation, and model animation. The main focus is on discrete event simulation. Random number generation; random variety generation, learning components of simulation and the simulation of simple systems are also in the scope of this course. Applications to manufacturing, service industries, and transportation and layout problems are also examined.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course provides students with basic coverage of topics in quality assurance and management. Principles of quality control systems, process control concepts, control charts for variables and attributes, process capability analysis, specification and tolerances, and acceptance sampling plans, are among the topics discussed.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course provides basic concepts and tools of reliability theory related to engineering systems such as life distributions, reliability function, failure rate, failure times, maintainability, reliability allocation and optimization, failure mode and effect analysis, and fault tree analysis.

This course studies the basic concept of information systems and explores how industrial engineering tools and methodologies can be utilized in the design, implementation and use of these systems.. Focus on database management systems and the design, implementation and use in relation to such systems. Course topics include relational database models, data modeling, logical database design, SQL (Structural Query Language) for relational databases and relational integrity rules. System analysis, system requirement analysis, system architecture and design of workflow management systems are among the subjects discussed. Special emphasis is given to integrated information systems in the production and distribution of goods and services.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

Systems Thinking lays the groundwork for Industrial Engineering (IE) practice; it is a pre-requisite for making sense of human behavior, structuring issues and defining problems. Without an adequate conception of systems: irrelevant or ineffectual problems may be addressed, the link from quantitative analysis to management practice will be incomplete; designs will not work out as planned, and improvements will fail to succeed. This course addresses systems thinking and systems theory in a formal and systematic treatment.

• Industrial Engineering | Curriculum | Prerequisites / Conditions Graph

This course covers history, define and classification of innovation, create innovation culture and implement Blue Ocean Strategy. Case studies selected for this course are from diverse areas such as incremental innovations/radical innovations/architectural innovations/market Innovation/category innovation/ process innovation and business model innovation.

This course addresses the basic principles of project management, tools and techniques. After the review of state of the art issues, students learn techniques that can reinforce project planning and controlling skills, and enrich leadership skills. The phases of the projects as initiation, planning, execution control and closure will be nalyzed in systems approach, and students will learn project-planning techniques with a project management software.

This course includes topics such as single person or group decision making under multi-criteria decision making (MCDM). Students will get knowledge about basic terms of decision making and the types of decision making problems. They will learn how to structure and model decision making problems, how to solve these problems by an appropriate solving method.

This course provides a study of the principles and application of Computer Integrated Manufacturing (CIM) systems. The basic principles of CIM, Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), automation systems, Flexible Manufacturing Systems (FMS), manufacturing planning systems are the topics covered in this course.

This course deals with data analytics concepts with an emphasis on engineering applications. The term data analytics refers to the process of applying computer based methodology to extract knowledge from very large data sets. Topics include data preparation, exploratory data analysis, visualization, linear regression, classification, tree based methods, cluster analysis, and association rules. The software that will be used in this course is R.