This course gives the students in the master's degree program the opportunity to write a thesis and discuss it with their advisor.

This course is mandatory for doctoral students and gives them the opportunity to write a thesis and discuss it with their advisor.

This course deals with arranging, analyzing, and presenting numerical/categorical data. Also, large data analysis using software SPSS is covered.

This course aims to provide the student with an introduction to economic decision making. This covers the basics of economic analysis from an engineering perspective, dealing with the principles and methods for analyzing the economic feasibility of alternatives and for making selection decisions among them. The student will learn how to perform economic evaluation and develop cost models for problem solving. Concepts in this class are equally applicable to engineering, business, and financial systems problems.  

This course covers all the concepts’ structure, and technical environments of information systems focusing on their application from the user's point of view.  

This course will focus on an integrated information system and its interaction with business processes to maximize the productivity of the organization as a whole. It will also help both functional area and IT managers understand how packaged ERP systems achieve the goal of an integrated application system by providing business managers with accurate, consistent, and current data.  

This course let students understand the principles and basic techniques of data communication focusing on the physical layer, data link layer, network layer of OSI models, and TCP/IP.  

This course aims to enhance the students' logical and conceptual competence and equip them with the ability to solve actual problems by learning how to approach and derive solutions to problems in the management aspects of corporate organizations based on mathematical logic.  

The course lets students cultivate the competency required for the strategic establishment and planning of the corporate organization by studying new issues, various models, and techniques focusing on the strategic concept in management.

This course studies various latest network structures, protocols, and performance analyses from a simple switching network to a multi-media network that handles multimedia traffic.  

The course provides theories of technology management including technological innovation, technological forecasting & planning, technology evaluation, technology diffusion, and technology utilization, and cultivates students with the capability of understanding and applying systematic approach and analytic methods for aiding decision making in technology management.  

In this course, students will learn the basic theory of the database such as the E-R model, database design, normalization, and indexing. Especially, basic and advanced SQL usage will be covered. Students will practice how to use the Oracle database system, which is the dominant database system in the world.  

The purpose of this course is to provide a comprehensive treatment of commonly used and more recently applied methodologies for technology investment decision making. It introduces students to an in-depth treatment of a wide variety of decision-making methodologies focused on the subject of investing in IT based on the knowledge of Engineering Economy. Delivery is primarily made via a mixture of lectures and project presentations.  

This course aims to learn how to find and model the relations, patterns, and rules from instances in lots of data. The main topics of this course are classification using a decision tree, Market basket analysis, and neural network algorithms and methods to utilize software to analyze real data using these algorithms are covered in this course.

The course provides theories of service management including service strategy, service design and development, service operation, and service evaluation, and cultivates students with the capability of understanding and applying systematic approaches and quantitative models of service science and engineering.  

This course aims to examine the organization from a structural, human, resourceful, political, and symbolic point of view by focusing on people and the organization, which are the main areas for achieving organizational performance. It also covers the performance management/evaluation system and coaching methodology, which have become more important after introducing the annual salary system.

This course teaches the students the characteristics of the general or IT Projects and project management planning, execution and control methodology based on PMBOK(Project Management Body of Knowledge). Students collects the various information about CCPM (Critical Chain Project Management) or Agile project management methods which are prevailing nowadays in various project management and write a small paper about the CCPM or Agile methods.  

The major objective of the course is to introduce the basic concept and theories of investment by covering corporate finance, investment theory, and finance as one integrated concept. This course covers the structure of interest rates, the concept of risk, risk management, analysis of investment plans, and asset valuation, which are the core of investment. It also examines the investment decision-making process for bonds and stocks and introduces the concept of pricing derivatives such as futures and options.

This course let students be skillful in the procedures and tools used for developing software. It covers the software development process and management methodologies such as requirements analysis, design, architecture, process, test, and maintenance. It also deals with up-to-date techniques such as CMM, Agile and cost-estimating techniques.  

This course studies how to calculate the cost of hardware, software, and network for estimating the cost of information systems. In this course, we study in detail software cost estimation techniques for the consulting project, the software development project, the software maintenance project, the software operation project, and the database construction project.  

This course lets students who have not majored in industrial information systems before knowing what the industrial information system major and what methodologies is have been used to solve problems. It covers not only industrial engineering and management science methodologies but also basic concepts of management information systems and technology management areas. In other words, this course aims to introduce the field of industrial information system engineering.  

This course deals with the Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), and Data Envelopment Analysis (DEA), which are widely used in IT policy decision analysis. This course introduces AHP, ANP, and DEA techniques and studies the latest applied papers related to them. Also, the students discover real problems related to AHP, ANP, or DEA, and write a short application paper.  

This course deals with the Genetic Algorithm, Tabu Search, and Simulated Annealing as metaheuristic techniques. In the Genetic Algorithm, solution expression, cross-operation, and mutation method are introduced, and Tabu Search and Simulated Annealing techniques are introduced. This course introduces the latest papers related to each technique and learn the tools to implement them.  

This course studies various methodologies and evaluation theories of policy-making essential for developing various new technologies and establishing systems applying them through seminars.  

Social Network Analysis (SNA) analyzes the implications of social phenomena through the analysis of social relationships (or networks). The theoretical background, main concepts and methods of social network analysis, data collection, and analysis methods, etc., are covered. In addition, state-of-art research related to SNA is discussed. This course also develops the ability to collect and analyze data using SNA tools.

With the development of information systems, people can perform many tasks through information systems. Some of such tasks require the financial, biometric, or privacy-sensitive information. If those are exposed to malicious entities or altered without the legitimate permission, the owner of them can have great damage. This course deals with basic information protection to provide the availability of corporate information systems while such sensitive information is secured. Basic passwords and authentication, and security for various applications are covered. This course requires prior knowledge of basic computer systems, computer networks, database systems, programming languages, and various IT applications.  

Students learn hacking programs, malicious codes, and DDoS attack tools, etc. used for hacking to prevent information leakage due to hacking and study security techniques to respond to them.

In this course, students can use R, a statistical analysis software, and learn techniques to analyze multivariate data such as regression analysis, principal component analysis, canonical correlation analysis, discriminant analysis, and so on.  

This course provides the modeling and simulating method for the various systems like physical manufacturing and material handling systems, business systems, computer system and social systems. The students learn to how to use the simulation software Arena and perform the case based simulation study for their own selected system and write a paper or a report using the results.  

This course aims to provide understanding of modern neural networks. Their representative models including basic neural networks, convolutional and recurrent neural networks will be covered, and also, various real-world applications will be introduced.  

In this course, we learn how to store and manage Big data. First, we analyze the various data types and large-scaled data volume managed by Big companies such as Google, Facebook, and Amazon. Therefore, we understand the necessity of the mechanism storing and managing Big data. Next, we study theory of databases and distributed databases for managing structured data and practice some practical examples using a representative commercial database system (Oracle). Finally, we study representative NoSQL systems such as HBase, Cassandra, MongoDB. For individual and group projects, each student selects one of NoSQL systems. Students survey the advantages and disadvantages of the selected system comparing with the other systems and utilize the system for managing real sample data.  

This course introduces the basic concepts and various methodologies for UX / UI design, and the process of designing and analyzing the user experience including UX/UI guideline, Components, User research methodologies and design for AI device

Students study various methodologies and practical examples for analyzing textual data. It covers most of the text data analysis techniques from naive frequency-based analysis to word representation, document representation, document classification/grouping, and sequence data analysis.  

This course covers the basic theory of Human-Computer Interaction (HCI) and interaction techniques using various modalities. In addition, students will learn about various multi-modal, cross-domain interactive applications based on the latest machine learning and deep learning technologies.  

Modern cryptography, which began with the proposal of a public key cryptography system in the 1970s, was established based on solid cryptography theory. This course deals with not only the fundamentals of modern cryptography but also the state-of-the-art cryptographic technologies. Topics covered are the theoretical foundations of pseudo-random number functions, hash functions, message authentication codes, symmetric keys, and public key cryptography as well as fully homomorphic encryption and the zero-knowledge proofs, which is the core technology in modern cryptocurrencies. This course is recommended to those who already have taken the information security course.  

This course aims to provide an understanding of design and creation of data visualizations based on available data and expected a goal. It covers data modeling, data aggregation, filtering, mapping data attributes to graphical attributes, and strategic visual encoding. It also lets students evaluate the effectiveness of visualization designs and think critically about each design decision.  

This course covers the basic theory of Human-Computer Interaction (HCI) and interaction techniques using various modalities. In addition, students will learn about various multi-modal, cross-domain interactive applications based on the latest machine learning and deep learning technologies.  

Financial industry is one of the highly regulated areas in order to protect unsophisticated consumers. However, new IT technologies can enable financial transactions in more convenient but unregulated ways. Recently, some of strong financial regulations are alleviated temporarily or permanently in order to expedite innovations with IT technology. This course will introduce the traditional financial regulations. After that, new financial services and new way of financial transactions will be covered. The technological and regulatory issues will be discussed from the traditional financial business to the up-to-date FinTech servies across major financial industries, including banking, security, insurance, and payment systems. FinTech including but not limited to Internet Banking, Crowdfunding, Open Banking, and new payment systems will be discussed.  

This course will introduce the basic ideas and techniques underlying artificial intelligent systems. The techniques and tools you learn in this course apply to a wide variety of artificial intelligence problems. The student will have a chance to discuss the issues and applications related to artificial intelligence.