For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESM4112 | Smart Healthcare Systems | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
| The course "Smart Healthcare Systems" focuses on the significant role these systems play in innovating and enhancing the efficiency of modern healthcare services. By collecting, analyzing, and utilizing health data, these systems enable personalized treatment, disease prediction and prevention, and overall improvement in healthcare services. The course delves into the integration of cutting-edge technologies like big data, artificial intelligence, machine learning, and the Internet of Things (IoT). This course aims to explore various data analysis techniques actively applied in data-based healthcare systems, examine their use cases, and learn to implement them in real-world scenarios. The course includes the following modules: 1. Introduction to Smart Healthcare Systems: This part provides an overview of the basic concepts, history, and recent advancements in smart healthcare. 2. Integration of Technology and Healthcare Management: This part explores how technologies like wearable devices, IoT, AI, and big data are applied in healthcare. 3. Data Analysis and Technical Approaches: This is the core part of the course, focusing on the technical aspects of health data collection, processing, and analysis. It introduces advanced technologies for data analysis, including machine learning, deep learning, Markov Decision Processes (MDP), reinforcement learning, and graph neural networks. 4. Case Studies in Smart Healthcare | |||||||||
| ESM4112 | Smart Healthcare Systems | 3 | 6 | Major | Bachelor/Master | Industrial Engineering | Korean | Yes | |
| The course "Smart Healthcare Systems" focuses on the significant role these systems play in innovating and enhancing the efficiency of modern healthcare services. By collecting, analyzing, and utilizing health data, these systems enable personalized treatment, disease prediction and prevention, and overall improvement in healthcare services. The course delves into the integration of cutting-edge technologies like big data, artificial intelligence, machine learning, and the Internet of Things (IoT). This course aims to explore various data analysis techniques actively applied in data-based healthcare systems, examine their use cases, and learn to implement them in real-world scenarios. The course includes the following modules: 1. Introduction to Smart Healthcare Systems: This part provides an overview of the basic concepts, history, and recent advancements in smart healthcare. 2. Integration of Technology and Healthcare Management: This part explores how technologies like wearable devices, IoT, AI, and big data are applied in healthcare. 3. Data Analysis and Technical Approaches: This is the core part of the course, focusing on the technical aspects of health data collection, processing, and analysis. It introduces advanced technologies for data analysis, including machine learning, deep learning, Markov Decision Processes (MDP), reinforcement learning, and graph neural networks. 4. Case Studies in Smart Healthcare | |||||||||
| ESM4113 | Design for Reliability | 3 | 6 | Major | Bachelor/Master | 1-2 | English | Yes | |
| Reliability is the ability of a product to function properly, i.e. within specified performance limit, for a specified period of time under the life cycle application conditions. Knowledge of reliability concepts and principles, as well as risk assessment, mitigation and management strategies prepare students to contribute effectively to reliability-based product design and life cycle management. This course teaches the fundamental knowledge and skills in reliability as it pertains to the design, manufacture, and use of electrical, mechanical and electro-mechanical products. Topics cover the suitability of the supply chain members to contribute towards development, manufacturing, distribution and support of reliable products; efficient and cost-effective design and manufacture of reliable products; FMMEA, reliability prediction and reliability allocation; how to plan and implement product testing to assess reliability; how to analyze degradation, failure, and return data to estimate fundamental reliability parameters. | |||||||||
| ESM4113 | Design for Reliability | 3 | 6 | Major | Bachelor/Master | 1-2 | Industrial Engineering | English | Yes |
| Reliability is the ability of a product to function properly, i.e. within specified performance limit, for a specified period of time under the life cycle application conditions. Knowledge of reliability concepts and principles, as well as risk assessment, mitigation and management strategies prepare students to contribute effectively to reliability-based product design and life cycle management. This course teaches the fundamental knowledge and skills in reliability as it pertains to the design, manufacture, and use of electrical, mechanical and electro-mechanical products. Topics cover the suitability of the supply chain members to contribute towards development, manufacturing, distribution and support of reliable products; efficient and cost-effective design and manufacture of reliable products; FMMEA, reliability prediction and reliability allocation; how to plan and implement product testing to assess reliability; how to analyze degradation, failure, and return data to estimate fundamental reliability parameters. | |||||||||
| ESM4114 | Text Analytics and Natural Language Processing | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
| This course “Text Analytics and Natural Language Processing” covers the methods to analyze the structure and meaning of language and learns various algorithms and techniques based on this understanding. The core content includes text-preprocessing techniques, traditional text mining, various language models, and word embeddings, and extends to the latest language models based on neural networks and transformer structures. Specifically, the content of this course includes: 1. Text Preprocessing: The first step in NLP, text preprocessing involves basic tasks to process text data. This includes tokenization, regularization, and stop words removal. 2. Text Mining: Introducing various NLP tasks, focusing on text classification models that can be easily implemented through TF-IDF and traditional classification models. 3. Probabilistic Language Models and Word Embeddings: Students will learn various NLP models focusing on how computers understand and interpret human language. These models include probabilistic language models and word embeddings. 4. Language Modeling with RNNs and Seq2Seq: The course then explores language modeling using Recurrent Neural Networks (RNNs) and applies it to various NLP tasks. It also examines Seq2Seq models for text generation and machine translation. 5. Transformer and Large Language Models: Learning about transformer structures and language models based on them, like BERT, GPT, etc. | |||||||||
| ESM4114 | Text Analytics and Natural Language Processing | 3 | 6 | Major | Bachelor/Master | Industrial Engineering | Korean | Yes | |
| This course “Text Analytics and Natural Language Processing” covers the methods to analyze the structure and meaning of language and learns various algorithms and techniques based on this understanding. The core content includes text-preprocessing techniques, traditional text mining, various language models, and word embeddings, and extends to the latest language models based on neural networks and transformer structures. Specifically, the content of this course includes: 1. Text Preprocessing: The first step in NLP, text preprocessing involves basic tasks to process text data. This includes tokenization, regularization, and stop words removal. 2. Text Mining: Introducing various NLP tasks, focusing on text classification models that can be easily implemented through TF-IDF and traditional classification models. 3. Probabilistic Language Models and Word Embeddings: Students will learn various NLP models focusing on how computers understand and interpret human language. These models include probabilistic language models and word embeddings. 4. Language Modeling with RNNs and Seq2Seq: The course then explores language modeling using Recurrent Neural Networks (RNNs) and applies it to various NLP tasks. It also examines Seq2Seq models for text generation and machine translation. 5. Transformer and Large Language Models: Learning about transformer structures and language models based on them, like BERT, GPT, etc. | |||||||||
| ESM4115 | ESG Management Introduction | 3 | 6 | Major | Bachelor/Master | 1-2 | Korean | Yes | |
| This lecture deals with the changes in the business environment created by ESG. In order to understand ESG management, we cover the meaning and importance of that, ESG management system and operational tasks, as well as external conditions and pressures that have made the importance and urgency of ESG management recognized. To this end, we examine the content and characteristics of major ESG-related initiatives as well as trends in the integration of ESG global disclosure indicators. Next, we cover ESG management practices. Here, we cover the theoretical background of ESG management and a systematic approach to sustainability management, environment and energy management, safety management, and social responsibility management, which are the core of ESG management. In sustainability management practice, we look at the understanding of corporate social responsibility(CSR) and corporate sustainability, which are fundamental concepts of ESG management, as well as the evolution of these concepts according to changes in business conditions and the process of forming balance between economic and social performance. In this way, an integrated strategy for internalizing sustainability is presented. Plus, the circular economy and the creating shared value (CSV) are discussed in an effort to connect ESG with business and create a blue ocean through ESG management, and the role and tasks of the 4th industrial revolution technology to support ESG management are also pointed out. | |||||||||
| ESM4115 | ESG Management Introduction | 3 | 6 | Major | Bachelor/Master | 1-2 | Industrial Engineering | Korean | Yes |
| This lecture deals with the changes in the business environment created by ESG. In order to understand ESG management, we cover the meaning and importance of that, ESG management system and operational tasks, as well as external conditions and pressures that have made the importance and urgency of ESG management recognized. To this end, we examine the content and characteristics of major ESG-related initiatives as well as trends in the integration of ESG global disclosure indicators. Next, we cover ESG management practices. Here, we cover the theoretical background of ESG management and a systematic approach to sustainability management, environment and energy management, safety management, and social responsibility management, which are the core of ESG management. In sustainability management practice, we look at the understanding of corporate social responsibility(CSR) and corporate sustainability, which are fundamental concepts of ESG management, as well as the evolution of these concepts according to changes in business conditions and the process of forming balance between economic and social performance. In this way, an integrated strategy for internalizing sustainability is presented. Plus, the circular economy and the creating shared value (CSV) are discussed in an effort to connect ESG with business and create a blue ocean through ESG management, and the role and tasks of the 4th industrial revolution technology to support ESG management are also pointed out. | |||||||||
| ESM4116 | ESG management strategy and practice | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
| ESG aims to improve corporate sustainability and corporate value through three elements: environment, society, and governance. Plus, ESG is a management ‘strategy’ and an ‘indicator’ for judging companies. However, recent rapid changes in corporate management conditions, such as the progress of standardization/regulation of disclosure, the expansion of the importance of supply chain management, and the imposition of carbon border adjustment, may cause companies and organizations to pay attention only to the regulatory response aspect, which may be insufficient for securing the ultimate goal, “sustainability”. Therefore, in this study, we aim to conduct strategic and practical research to suggest solutions to corporate and organizational problems based on ESG management theory. The purpose of this course is as follows. − Understand ESG management through balanced education of theory and cases − Strengthening practical skills through use and experience of checklists, processes, and methodologies that can be implemented in companies − Expanding and presenting self-learning through assignments The learning contents of this course are as follows. − ESG standardization trends − Local SDGs and ESG − Socially responsible investment − Social value creation and socio-technical system − Sustainability report (ESG report) analysis | |||||||||
| ESM4116 | ESG management strategy and practice | 3 | 6 | Major | Bachelor/Master | Industrial Engineering | Korean | Yes | |
| ESG aims to improve corporate sustainability and corporate value through three elements: environment, society, and governance. Plus, ESG is a management ‘strategy’ and an ‘indicator’ for judging companies. However, recent rapid changes in corporate management conditions, such as the progress of standardization/regulation of disclosure, the expansion of the importance of supply chain management, and the imposition of carbon border adjustment, may cause companies and organizations to pay attention only to the regulatory response aspect, which may be insufficient for securing the ultimate goal, “sustainability”. Therefore, in this study, we aim to conduct strategic and practical research to suggest solutions to corporate and organizational problems based on ESG management theory. The purpose of this course is as follows. − Understand ESG management through balanced education of theory and cases − Strengthening practical skills through use and experience of checklists, processes, and methodologies that can be implemented in companies − Expanding and presenting self-learning through assignments The learning contents of this course are as follows. − ESG standardization trends − Local SDGs and ESG − Socially responsible investment − Social value creation and socio-technical system − Sustainability report (ESG report) analysis | |||||||||
| ESM4117 | Analysis on global supply chain crisis | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
| The global business environment and global supply chain is undertaking a structural change due to the COVID 19, Russia-Ukraine war, US-China economic and technology war, US Inflation Reduction Act and Chips and Science Act together with Chinese export control of key minerals and materials for lithium battery. As the result, the global supply chain is in a status of crisis. The US Administration enacted IRA and CSA respectively. The guardrail of the IRA and CSA is providing investment incentive to manufacturers and tax incentive to consumers by strictly regulating the participation of China in terms of investment equity participation and supply of key materials and prohibit any expansion of production line of semiconductors in the entity of concern, China. The global companies of Korea, Japan, and EU should seek new source of minerals and materials for producing lithium battery and divert the destination of FDI. India, Indonesia, Vietnam in Asia and Hungary, Poland, Check and Slovakia in Europe are emerging as new destination of FDIs. Korean global companies of semiconductors, automobile and electric batteries have to respond actively to the structural change of global business environment and global supply chain crisis by diversifying the FDI destinations. The assignment of “analysis on global supply” chain will provide to students an opportunity to analyze global business and investment environment global supply chain crisis and re-globalization. | |||||||||
| ESM4117 | Analysis on global supply chain crisis | 3 | 6 | Major | Bachelor/Master | Industrial Engineering | Korean | Yes | |
| The global business environment and global supply chain is undertaking a structural change due to the COVID 19, Russia-Ukraine war, US-China economic and technology war, US Inflation Reduction Act and Chips and Science Act together with Chinese export control of key minerals and materials for lithium battery. As the result, the global supply chain is in a status of crisis. The US Administration enacted IRA and CSA respectively. The guardrail of the IRA and CSA is providing investment incentive to manufacturers and tax incentive to consumers by strictly regulating the participation of China in terms of investment equity participation and supply of key materials and prohibit any expansion of production line of semiconductors in the entity of concern, China. The global companies of Korea, Japan, and EU should seek new source of minerals and materials for producing lithium battery and divert the destination of FDI. India, Indonesia, Vietnam in Asia and Hungary, Poland, Check and Slovakia in Europe are emerging as new destination of FDIs. Korean global companies of semiconductors, automobile and electric batteries have to respond actively to the structural change of global business environment and global supply chain crisis by diversifying the FDI destinations. The assignment of “analysis on global supply” chain will provide to students an opportunity to analyze global business and investment environment global supply chain crisis and re-globalization. | |||||||||
| ESM4118 | Applied Programming-Commerce Advertising Technology (AdTech) Practice | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
| This course is for students who are already familiar with computer programming to learn about how data scientists use programming in the real world. Programming is practiced using advertising technologies mainly used in retail and e-commerce as examples. In retail and e-commerce advertising, a variety of data is collected in real-time, including clicks, impressions, and purchase conversions. In this class, students will learn these data and related advertising technology theories, and practice advertising modeling and advertising optimization using the Python language. | |||||||||
| ESM4118 | Applied Programming-Commerce Advertising Technology (AdTech) Practice | 3 | 6 | Major | Bachelor/Master | Industrial Engineering | Korean | Yes | |
| This course is for students who are already familiar with computer programming to learn about how data scientists use programming in the real world. Programming is practiced using advertising technologies mainly used in retail and e-commerce as examples. In retail and e-commerce advertising, a variety of data is collected in real-time, including clicks, impressions, and purchase conversions. In this class, students will learn these data and related advertising technology theories, and practice advertising modeling and advertising optimization using the Python language. | |||||||||
| ESM5001 | Queueing Theory | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
| This course covers the analysis of the queueing systems and their applications. Stochastic nature of the queueing systems are analyzed and various performance measures are derived. | |||||||||