학부교과목


  • MGE201 Operations ResearchⅠ [계량경영학Ⅰ]
    This course is an introduction to the key aspects of operations research methodology. Students will model and solve a variety of problems using deterministic and stochastic operations research techniques. Topics include basic theory, modeling, the use of computer tools, and interpreting results.
  • MGE205 Introduction to Financial Engineering [금융공학개론]
    This course introduces the basic knowledge on various financial instruments as well as quantitative models for finance. The main topics include: equities, fixed-income securities, derivatives including options and futures, asset pricing models, and investment management. In addition, we will learn how to implement basic financial engineering problems using Python.
  • MGE206 Introduction to Industrial & Management Engineering[산업경영공학의 이해]
    Management engineering links engineering, science, and management to plan and operate management strategy of corporations. This course will cover a variety of models and methods in the field of management engineering, ranging from qualitative frameworks to quantitative techniques. Students are expected to develop the capability to synthesize engineering technology and management strategy.
  • MGE207 Data Science Programming[데이터 사이언스 프로그래밍]
    This courses focuses on Python as a programming language and covers basic and advanced topics related to algorithm design and data management. The first part of the course focuses on fundamental data structures (e.g., stacks, queues, trees, heaps) and algorithms (e.g., recursion, sorting) for programming. In the second part, the course looks at advanced data structures, such as graphs, and advanced aspects related to data acquisition and processing, e.g., natural language and text processing or tracking and processing of live Twitter streams. The objective of the course is to give students the ability to design advanced algorithms for acquiring, storing and processing effectively data regardless of the application domain.
  • MGE209 Operations Management [생산운영관리]
    Operations management is basically concerned with the production of quality goods and services, and how to make efficient and effective business operations. It involves subjects in the analysis of production planning, inventory and quality control, cost and performance analysis, and supply chain management.
  • MGE303 Data Mining[데이터마이닝]
    Data mining is comprised techniques from statistics, AI, and computer science. It is applied not only to conventional engineering and science problems, but also to various business areas such as manufacturing, marketing and finance. This course introduces basic data mining problems (clustering, classification, and association analysis) and the respective algorithms and techniques. In addition, students will learn about actual business problems, goals, and the environment in which data mining is applied. Cases in various areas will be studied. Students are strongly encouraged to identify and solve real world business problems using data mining techniques so that they improve their relevance to human interface design.
  • MGE313 MGE305 Operations Research Ⅱ[계량경영학 Ⅱ]
    Operations Research II is the second of a two-course sequence that introduces students to models commonly used in the analysis of complex decision-making problems. Modeling approaches and fundamental solution methodologies will be emphasized. This course covers a variety of ways in which deterministic and stochastic models in Operations Research can be used and applied to solve practical problems. Topics for this course include nonlinear and integer programming, dynamic programming, Markov decision processes, and queueing theory.
  • MGE311 MGE308 Service Simulation[서비스 시뮬레이션]
    Service systems in transportation, retail, healthcare, entertainment, hospitality, and other areas are configurations of people, information, organizations, and technologies that operate together for specific functions and values. The field of Service Science is emerging as the study of complex service systems, and involves methods and theories from a range of disciplines, including operations, industrial engineering, marketing, computer science, psychology, information systems, design, and more. Effective understanding of service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. In this course, we will learn and apply concepts and methods in Service Science for service management and engineering.
  • MGE312 MGE313 Time-series Analysis[시계열 분석]
    This course introduces regression analysis and applications to investment models. Principal components and multivariate analysis. Likelihood inference and Bayesian methods. Financial time series. Estimation and modeling of volatilities. Statistical methods for portfolio management.
  • MGE362 MGE361 Quantitative Technology Management [계량 기술경영]
    Technology management is a set of management disciplines that allows organizations to manage their technological fundamentals to create competitive advantage. This course will cover a variety of topics and quantitative methods in the field of technology management. Students are expected to learn the ways of integrating data science into different types of problems in the field of technology management.
  • MGE404 MGE362 Statistical Quality Management[통계적 품질관리]
    The objective of this course is to teach various methods that can be used for improving the quality of products and processes. Topics for this course are quality system requirements, designed experiments, process capability analysis, measurement capability, statistical process control, and acceptance sampling plans.
  • MGE404 Data-driven Process Management[데이터 기반 프로세스 관리]
    Business processes are ubiquitous in modern organizations and their execution is increasingly supported by advanced information systems, which make available a large amount data related to their design and execution. The first part of this course focuses on the typical phases of business process management in an organisation, that is, business process identification, business process modelling (using BPMN 2.0), and business process analysis and improvement. The second part focuses on process mining, that is, a state of the art technique to extract knowledge about business processes, e.g., process models, from the logs of the IT systems supporting their execution.
  • MGE411MGE406 Applied Machine Learning[기계학습 응용]
    This course gives you understanding of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more state-of-the art topics such as ensembles and deep learning. Students will be able to apply predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). By the end of this course, students will be able to identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write their own code (Python, R or Matlab) to carry out an analysis.
  • MGE412 Quantitative Financial Planning [정량적 재무관리]
    In this course, we will learn about the stochastic process on the continuous time line and the theoretical approaches for finding financial derivatives values. This course will mainly focus on understanding main properties on Brownian motion and the derivative pricing theory with a Black-Scholes_Merton approach and a probabilistic approach. This course will focus mainly on the theory but examines some estimation methods as well empirical evidence.
  • MGE413 Fixed Income Analysis [이자율 상품 분석]
    This course is designed to introduce the fixed income market. Students are going to understand the time value of money and the relation between price and yield. The derivatives products underlain by money or bond such as swaps or options will be introduced as well. Most of explanations will be applied to practical market situations.
  • MGE421 Blockchain-based System Engineering [블록체인 기반 시스템]
    This course introduces blockchain technology. The objective of this course is to cover the basics of blockchain technology as a technology for designing and implementing cross-organisational information systems. The course starts with an overview of blockchain technology and its emergence in the field of cryptocurrency and then will focus more extensively on designing systems using blockchain. The course will look both at applications of blockchain in real world scenarios and at the more technical aspects related with the implementation of such systems.
  • MGE422 Social Network Analysis [사회 연결망 분석]
    This course introduces students to the basic concepts and analysis techniques in (online) social network analysis. After completing this course, students will learn how to (1) analyze large-scale online user-generated data on social networks (e.g., social media, such as Facebook or Twitter) and (2) apply machine learning techniques to discover knowledge from online social networks.
  • MGE470 MGE450 Project Lab. [프로젝트 랩]
    Students and strategic partners from industry will work in project teams and undertake management engineering industrial projects. The teams must aim to disseminate completed project outcomes to industry. The progress of each project will be reviewed based on formal presentations
  • MGE470 Special Topics in MGEⅠ [MGE 특론Ⅰ]
    This course is designed to discuss contemporary topics in Management Engineering. Actual topics and cases will be selected by the instructor and may vary from term to term.
  • MGE471 Special Topics in MGE Ⅱ [MGE 특론Ⅱ]
    This course is designed to discuss contemporary topics in Management Engineering. Actual topics and cases will be selected by the instructor and may vary from term to term.
  • MGE472 Special Topics in MGE Ⅲ [MGE 특론 Ⅲ]
    This course is designed to discuss contemporary topics in Management Engineering. Actual topics and cases will be selected by the instructor and may vary from term to term.