1st YEAR / FALL SEMESTER
MIS 101 – Yönetim Bilişim Sistemlerine Giriş (Introduction to Management Information Systems)
This course introduces compulsory topics in the 4-year undergraduate program. The topics covered include data, information and knowledge, information systems in business such as enterprise applications, IT infrastructure, security in information systems, managing knowledge.
1st YEAR / SPRING SEMESTER
MIS 102 – İşletme ve Yönetim Prensipleri (Principles of Business and Management)
This course addresses various aspects of the external business environment, such as the global market, ethics and social responsibility, business ownership, and entrepreneurship. Additionally, the course covers different dimensions of management, including decision-making and leadership, employee control, communication and conflict management, as well as teamwork and team management. Fundamentals of marketing management are also included among the topics.
2nd YEAR / FALL SEMESTER
MIS 207 – Veri Bilimi için Programlama (Programming for Data Science)
Programming for Data Science course is designed to equip students with the programming skills and foundational knowledge necessary to excel in data science. This course covers all essential aspects of using high level language such as R, and it includes introduction to programming, data and data manipulation.
2nd YEAR / SPRING SEMESTER
MIS 202 – Bilgi ve Yönetim Ekonomisi (Economics of Information and Management)
This course provides a thorough exploration of economic tools and analytical methods available to managers for effective business decision-making. Economics equips decision-makers with a diverse set of tools for making and analyzing managerial decisions and provides a framework to comprehend how changes in the business environment impact decision-making. The course includes such topics as consumer choice and demand, technology and production, profit maximization, cost minimization, and market structures such as perfect competition, monopoly and oligopoly.
MIS 204 – Bilgisayar Ağları (Computer Networks)
Basics of data communication, basic protocols including HTTP, FTP, POP, IMAP, UDP, DNS, computer networks; application, transport, network and data link layers of the OSI basic reference model, IP, flow control, congestion control, TCP/IP, ISP and hierarchic Internet structure.
MIS 208 – Veri Analizine Giriş (Introduction to Data Analysis)
This course is designed to develop the statistical software knowledge required for data analysis for Management Information Systems students and to introduce the data and its properties that will help students succeed in data analytics and modeling courses. Students will learn to use the basic software and software packages required for data analysis.
3rd YEAR / FALL SEMESTER
MIS 315 – Veri Analitiği I (Data Analytics I)
This course is the first part of a two-semester course and provides data analytics methods that are required to extract knowledge from business data. Extracted knowledge is used by business managers to make effective decisions in understanding customers, for managing default risk, fraud, or acquiring, managing, retaining or winning back customers. Both theory and applications are covered.
MIS 303 – Veritabanı Yönetim Sistemleri (Database Management System)
This course introduces relational databases, data types, tables, queries, relationships; building entity-relationship models; introduction to relational algebra and Structured Query Language (SQL), functional dependency and normalization; NoSQL databases.
MIS 305 – Veri Analizi: Modelleme (Data Analysis: Modelling)
This course introduces students to the fundamental techniques of data analysis and statistical modeling, with a focus on applications relevant to business and economics. Topics include regression analysis, model specification, hypothesis testing, and dealing with deviations from classical assumptions. The course blends theory with practical applications, providing hands-on experience with R to help students develop the essential skills for analyzing and interpreting data in a business environment.
MIS 307 – Karar Analizi I (Decision Analysis I)
This course is the first part of the two-semester decision analysis sequence, focusing on managerial and consumer decision-making behavior under certainty. It introduces students to quantitative techniques used to gain insight into business and consumer decisions. Topics include graphical and simplex methods for solving linear programming problems; sensitivity analysis and shadow prices, duality, the big M method, integer programming, goal programming, nonlinear programming with equality constraints, the Kuhn-Tucker optimality conditions, and quadratic programming.
3rd YEAR / SPRING SEMESTER
MIS 314 – Veri Analitiği II (Data Analytics II)
This course is the second part of a two-semester course and provides data analytics methods that are required to extract knowledge from business data. A review of fundamental methods, evaluation of regression approaches, possible violation of major assumptions and the possible solutions, support vector machines, similarity measures, and clustering will be covered. Extracted knowledge is used by business managers to make effective decisions in understanding customers, for managing default risk, fraud, or acquiring, managing, retaining, or winning back customers. Both theory and applications are covered.
MIS 306 – Veri Analizi: Tahmin (Data Analysis: Forecasting)
This course provides an introduction to time series analysis and forecasting. Topics include time series visualization, decomposition, exponential smoothing methods, and ARIMA models. The course also covers time series regression and model comparison using accuracy measures. Emphasis is placed on practical implementation using the R programming language. Students will learn how to analyze, model, and forecast real-world time series data, as well as interpret model outputs. The course serves as a foundation for more advanced analytics and data science courses.
MIS 316 – Sistem Analizi ve Tasarım (System Analysis and Design)
This course covers the fundamental concepts and methods related to the analysis and design of information systems. Students learn system development processes, requirements analysis and modeling techniques, as well as the basic principles of database and process design. In addition, different types of diagrams and approaches to system development are examined within the scope of the course.
MIS 400 – Yaz Stajı (Summer Practice)
This course aims to help students reinforce their theoretical knowledge in the field of Management Information Systems through practical experience. During the summer internship, students take part in a real business environment and gain hands-on experience in areas such as information systems, software development, systems analysis, data management, and project management. Additionally, they develop an understanding of the dynamics of the business world, adapt to teamwork, enhance their communication skills, and gain awareness of professional ethics.
4th YEAR / FALL SEMESTER
MIS 415 – Kurumsal Uygulamalar (Enterprise Applications)
This course covers the information systems used in enterprise resource planning (ERP), supply chain management (SCM), customer relationship management (CRM), and knowledge management. Students learn the fundamental concepts, functions, and roles of these systems in business processes.
MIS 403 – İşletme ve Ekonomi için Makine Öğrenimi (Machine Learning for Business and Economics)
In recent years, machine learning techniques have been successfully applied to a wide range of problems across fields such as Economics, Finance, and Management. This course is designed to introduce students in the Management Information Systems program to fundamental machine learning methods and provide a critical understanding of their strengths and limitations. Topics include commonly used techniques such as classification, regression, and clustering. By the end of the course, students will have acquired essential knowledge of machine learning algorithms and will be able to apply them to real-world problems in business and economics contexts.
4th YEAR / SPRING SEMESTER
MIS 402 – Karar Analizi II (Decision Analysis II)
This course aims to build the foundation of decision analysis and decision making for students enrolled in the Management Information Systems program. At the end of the course, the students shall acquire basic knowledge about uncertainty, risk, utility, and decision under uncertainty. The content of the course includes Heuristics, Decision making with and without probabilities, Statistical Decision Theory, Utility Theory, how to measure utility and use utility function for decisions, decision trees, simulation, stochastic dominance and efficient frontier for decision makers.
MIS 408 – Mezuniyet projesi (Graduation Project)
In this course, students are expected to complete a theoretical or applied project paper related to information systems, data analytics or data analysis. Each student, under the guidance of an instructor, will prepare a paper during the semester and present the paper at the end of the semester. During the semester progress reports will be prepared and shared with the instructor.
Elective Courses of the Department of Management Information Systems
MIS 311 – İşletmeler için Veri Görselleştirme ve İletişimi (Data Visualization and Communication for Business)
Data visualization and communication have become vital skill for professionals working with data. This course introduces how to create impactful visualizations and effectively communicate insights using R to Management Information System Program students. It covers fundamental principles, techniques, and best practices for data visualization. At the end of the course, students enhance their ability to tell compelling stories through data and drive informed decision-making. In addition, they gain hands-on experience with R and its libraries, including ggplot2 and plotly to create data visualizations.
MIS 313 – Fiyatlama ve Gelir Analitiği (Pricing and Revenue Analytics)
Demand and revenue analytics refers to the set of practices and tools that firms in various industries use to quantitatively model consumer preferences, segment their market, and strategically optimize their product assortment, pricing, and promotional strategies, often in micro targeted or personalized manner. This course is designed to teach the fundamental principles and applications in pricing and revenue optimization and management. It equips students with the essential background knowledge, quantitative models, and data analysis skills so that they can identify and exploit opportunities for profit maximization in a variety of industrial and business contexts.
MIS 319 – İşletmeler için Siber Güvenlik Temel Konuları (Cyber Security Fundamentals for Business)
This introductory-level course provides an overview of computer security topics, with a focus on understanding the most common threat types and implementing basic protection systems for device, data, and network protection.
MIS 407 – İşletmeler için İleri Veri İletişimi Özel Konular (Topics in Data Communication for Business)
Data visualization and communication have become vital skill for professionals working with data. This course is designed to enhance students skills in data visualization and communication using the R programming language. Building upon the foundational knowledge of data driven decisions, this course delves into advanced techniques and strategies to effectively communicate complex data insights. Course specifically focused on interactive tables, interactive charts, network graphs and maps.
MIS 410 – İşletmeler İçin Metin Analitiği (Text Analytics for Business)
In today’s data-driven world, businesses struggle with massive amounts of unstructured information, especially text data. Specifically, unstructured text stands out as one of the most prevalent forms of such data. Consequently, mastering the skill of extracting business value from unstructured text is imperative for any business. This course empowers helps students to develop an understanding of the basics of text analytics through which they understand how to convert text data into an actionable information. Topics to be covered include text-normalization, tokenization, sentence boundary detection, n-gram, sentiment analysis and visualization.
MIS 412 – İşletmeler İçin Makine Öğrenmesinde Özel Konular (Topics in Machine Learning for Business)
Topics in Machine Learning for Business is designed for students who wish to deepen their understanding and expertise in applying recent advancements in machine learning (ML) to solve business challenges. This course covers cutting-edge ML techniques, real-world business applications, and strategic implementation of ML solutions to drive business value.
MIS 414 – Seçim Analizi (Choice Analysis)
For many disciplines that need to take demand dynamics into account, understanding individual choice behavior is essential. Discrete choice models capture the cognitive aspects of individual decision-making and have broad applications in a variety of fields, including applied economics, marketing, engineering, and urban planning. They have recently been employed in areas such as travel modes, coffee brands, telephone services, soft drinks, and various food products to predict demand in response to differing pricing and marketing strategies, as well as to determine how much consumers are willing to pay for qualitative improvements. Discrete choice models can also be used to study choices related to durable goods like automobiles, laptops, smartphones, refrigerators, air conditioners, and houses. This course presents the theory and practice underpinning the formulation and estimation of models of individual discrete choice behavior, with a specific focus on applications related to managerial decision-making. Students taking the course will develop an understanding of the theory, methods, application, and interpretation of probit, logit, multinomial logit, nested logit, and ordered logit models.
MIS 420 – Finansal Hizmetler için CRM ve Veri Analitiği (CRM and Data Analytics for Financial Services)
This course will analyze Customer Relationship Management (CRM) and Data Analytics methods with a special focus on financial services firms. Businesses, particularly in financial and service-related sectors, invested heavily in CRM systems starting in the 1990s, but most firms failed to reap the expected benefits. Our objective in this course is to understand CRM and business expectations and explore requirements for a successful CRM implementation. Given the importance of business analytics within CRM systems, our second objective would be to understand the data analytics methods businesses can utilize for higher profitability. This course is not intended to teach marketing strategies, but a basic level of marketing knowledge will be helpful to improve learning outcomes. The course’s primary focus is the application of data analytics techniques on customer data and why and how data analytics benefits businesses, especially financial services firms. Topics include but are not limited to: What CRM really is, CRM stages, Multi-channel integration, understanding customer and customer data, understanding customer attrition, application of data analytics methods such as visual exploration, decision trees, neural nets, and predictive models at all stages of customer lifecycle.