학사 과정 내 관련 교육과정 소개
| 교과목명 | 교과목소개 | 비고 |
|---|---|---|
| Computational Tools for Engineers | This course studies essential and practical computational tools and methods for engineers and designers. Students will improve their understanding of computer programming and IT applications in engineering design. Practical laboratories and projects with MATLAB and LabView will complement the course. | 디자인 및 인간공학부 |
| Experimental Design | The course describes procedures for conducting and analyzing human factors and ergonomics studies. It includes the fundamentals of research, experimental design alternatives, fitting and testing statistical models, and data interpretation and presentation. In terms of statistics, the primary focus is on linear regression (simple and multiple) and analysis of variance (single and multiple factor). | 디자인 및 인간공학부 |
| Manufacturing System Design & Simulation |
This course studies manufacturing system configuration, process flow design and their evaluation. The student will learn the basic concepts and methods of simulation techniques to design and evaluate manufacturing systems in which all workcells, including robots, material handling systems and other auxiliary equipment are functioning to maximum efficiency and productivity. | 디자인 및 인간공학부 |
| Probability (확률론) |
Laws of large numbers. Binomial, Poisson, gamma, univariate, and bivariate normal distributions. Introduction to stochastic processes. | 수리과학부 |
| Numerical Analysis (수치해석) |
Polynomial interpolation, Polynomial approximation, Orthogonal polynomials and Chebyshev polynomials. Least-squares approximations. Numerical differentiation and integration. | 수리과학부 |
| Ordinary Differential Equations (상미분방정식) |
linear systems, regular singular points. Analytic systems, autonomous systems, Sturm-Liouville Theory. | 수리과학부 |
| Discrete Mathematics (이산수학) |
permutations, combinations, networks, and graphs. Topics include enumeration, partially ordered sets, generating functions, graphs, trees, and algorithms. | 수리과학부 |
| Dynamical Systems (동적시스템) |
Qualitative properties of linear and nonlinear dynamical systems in both continuous and discrete time. | 수리과학부 |
| Stochastic Processes (확률과정론) |
Exponential Distribution and Poisson Process. Markov Chains. Limiting Behavior of Markov Chains | 수리과학부 |
| Parallel Computing | 분산 병렬 컴퓨팅은 대용량 빅데이터 처리에 있어서 가장 핵심적인 부분이다. 본 과목에서는 병렬 컴퓨팅의 기초에 대해 학습한다. | 전기전자 컴퓨터공학부 |
| Database Systems | 데이터베이스 수업에서는 데이터를 효율적으로 처리하기위한 SQL 언어 사용법 및 데이터베이스 내부의 시스템 구조에 대해 배운다. | 전기전자 컴퓨터공학부 |
| Machine Learning | 대용량 빅데이터에서 유의미한 정보를 추출해내는 여러 가지 기계학습 알고리즘에 대해 학습한다. | 전기전자 컴퓨터공학부 |
| Introduction to Algorithms | 알고리즘의 성능을 분석하는데 필요한 기초 이론 및 원리를 학습하고 알고리즘을 설계하는 방법을 배운다. | 전기전자 컴퓨터공학부 |
| Advanced Business Programming (고급 경영 프로그래밍) |
This subject examines the principles, techniques and methodologies for the design of business software systems using visual programming tools and the object-oriented approach. This subject describes the concepts of inheritance, encapsulation, construction, access control and overloading. Students will be provided with both the framework and the building blocks with which they can define and implement objects of their own and use them in conjunction with a visual programming system. | 경영학부 |
| 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. |
경영학부 |
| Database (데이터베이스) |
This course deals with the fundamental concepts of current database systems. Specific topics will include data modeling, database system architecture, and query processing. The course also covers advanced issues such as concurrency controls and disaster recovery methods. | 경영학부 |
| Process & Quality Management (생산과 품질관리) |
This course covers the approaches in quality improvement and implications in management responsibilities. Practical cases involving business processes will be analyzed and discussed in class. | 경영학부 |
| Data analysis & Decision Making (경영통계분석) |
The main goal of this course is to understand statistical analysis of data and to apply to various management issues in forecasting and planning. The topics include the basic concept of probability and statistics with the application of practical cases. |
경영학부 |