For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| COV7001 | Academic Writing and Research Ethics 1 | 1 | 2 | Major | Master/Doctor | SKKU Institute for Convergence | Korean | Yes | |
| 1) Learn the basic structure of academic paper writing, and obtain the ability to compose academic paper writing. 2) Learn the skills to express scientific data in English and to be able to sumit research paper in the international journals. 3) Learn research ethics in conducting science and writing academic papers. | |||||||||
| ERC5001 | Global Collaboration Research | 3 | 6 | Major | Master/Doctor | Engineering | Korean | Yes | |
| This class aims to enhance global competence as a researcher who study innovative growth fields through overseas dispatch of graduate students. Student’s who are dispatched overseas and carrying out joint research in world university will learn - to establish global network for future research - to strive for the creation of new industries in the field of sustainable development and innovative growth of mankind - to grow into global innovative leader with the competence of ‘Value creation’, ‘Convergence’, ‘Innovation’, and ‘Collaboration’ through innovation in creative convergence experiences that which cross the intercultural, interdisciplinary and intergeneration. In this class, students are expected to focus on projects during the overseas dispatch period to improve the quality of their research. Each researcher will present final report after they complete dispatch study and will be given their credit based on the presentation. | |||||||||
| ERC7001 | Understanding and Utilizing the Metaverse Platform | 3 | 6 | Major | Bachelor/Master/Doctor | Engineering | - | No | |
| The main purpose of this course is training that equips students with metaverse-based business or service planning capabilities based on understanding of the technical elements consisting of the metaverse and hands-on experiences with major platforms and related devices. Opportunities to understand the characteristics and uses of each technical component, to study the cases of major services, and to identify strengths and weaknesses from the user's point of view through experience are given, and furthermore, the ability to derive creative ideas for the use and improvement of metaverse services is cultivated. do. | |||||||||
| ERC7002 | Understanding and Utilizing NFT | 3 | 6 | Major | Bachelor/Master/Doctor | Engineering | - | No | |
| The main purpose of this course is to educate students to have business or service planning skills using NFT based on understanding of the concept and underlying technology of NFT, related digital economic ecosystem, examples of NFT projects, and hands-on practice of NFT production and sales. It includes a basic understanding of blockchain and cryptocurrency, which are the base technologies of NFT, and digital art and digital assets, which are the major existing applications. Through learning about major project cases, legal considerations, market analysis tips, and technology trends, students will develop the ability to derive creative ideas for a wide range of future uses. | |||||||||
| ETM5009 | Technology Planning | 3 | 6 | Major | Master/Doctor | 1-4 | Management of Technology | Korean | Yes |
| Present concept and method about strategic technology plan and estimation to link strategy of R & D and formation effectively. Studying with extent of R & D strategy and establishment plan, know-how and market estimate plan, management by objectives about research and development, R & D's measurement and estimation plan in corporate strategy | |||||||||
| ETM5065 | Technology Commercialization | 3 | 6 | Major | Master/Doctor | 1-4 | Management of Technology | Korean | Yes |
| Korean industries have to be changed from manpower-based into technology-based. R&D investment (input) is increased in fast speed, and so business output must be increased effectively and efficiently. The subject of "Technology Commercialization" will contribute to the level-up of R&D productivity (output/input) by accomplishing knowledges of basic concept, methodologies and various case studies in the area of technology commercialization. | |||||||||
| ETM5097 | AI Data based Technology commercialization exercise | 3 | 6 | Major | Master/Doctor | 1-4 | Management of Technology | - | No |
| This course introduces the basic theory and algotirhm of AI/Data-based technology commercialization methodologies. The underlying theories of KISTI's practical commercoalization models will be introduced with some practical examples. | |||||||||
| ETM5110 | Open Innovation and Commercialization | 3 | 6 | Major | Master/Doctor | 1-4 | Management of Technology | Korean | Yes |
| In this course, students will learn various types of open innovation cases (technology sourcing, venture investment, M&A, patent monetization, etc.) and factors of success and failure. In particular, this course invites open innovation managers or practitioners working in companies as special lecturers to provide practical knowledge and experience. Taking this course will help students discover topics for research papers and solve problems at the companies they work for | |||||||||
| SFC5007 | Smart Factory Cloud Platform | 3 | 6 | Major | Master/Doctor | Smart Factory Convergence | - | No | |
| This course provides an overview of many commercial cloud platforms, its high-level architecture and technology stack and guide students through these cloud platform concepts, its features and how cloud platform can be used to deploy, configure and manage cloud environments, software defined networks, and software defined storage solutions. Also, this course provide hands-on experience with cloud platform components for bare-metal provisioning, deployment and configuration management, networking, and monitoring. | |||||||||
| SFC5011 | Intelligent Robot and Artificial Intelligence Applications | 3 | 6 | Major | Master/Doctor | Smart Factory Convergence | - | No | |
| This course provides students with a working knowledge of methods for design and analysis of robotic and intelligent systems. And Artificial Intelligence (AI) focuses on the development and analysis of algorithms that learn and/or perform intelligent behavior with minimal human intervention. Particular attention is given to modeling dynamic systems, measuring and controlling their behavior, and making decisions about future courses of action. The content is necessarily broad, and the course level is introductory. | |||||||||
| SFC5015 | Industrial Artificial Intelligence | 3 | 6 | Major | Master/Doctor | Smart Factory Convergence | - | No | |
| Artificial Intelligence (AI) is a research field that studies how to realize intelligent human behavior on a computer. The ultimate goal of AI in the industry is to create computers that can learn, plan and solve problems autonomously. AI has been studied for more than half a century, but it is not possible to make computers as intelligent as humans in every way. But there are many successful applications. In some cases, computers with AI technology can be much smarter than we are. AI's main research topics in industry include problem solving, reasoning, planning, understanding natural language, computer vision, automatic programming, and machine learning. Of course, these themes are closely related to each other. For example, knowledge gained from learning can be used for both problem solving and reasoning. Indeed, problem-solving skills must be acquired through learning. Problem solving is also useful for reasoning and planning. In addition, methods developed in the field of pattern recognition can be used to solve both natural language understanding and computer vision. This course studies the most basic knowledge of AI understanding in industry. Students will learn some basic search algorithms such as knowledge representation and reasoning, pattern recognition, fuzzy logic, and neural networks for problem solving. | |||||||||
| SFC5018 | Smart Factory ConvergenceTechnologySeminar | 3 | 6 | Major | Master/Doctor | Smart Factory Convergence | Korean | Yes | |
| In this course, you will learn the latest issues in the field of smart factory convergence technology and expertise related to the application of intelligent information technology through seminars of external experts. Futuristic manufacturing system that combines smart factory convergence technologies such as cloud/edge computing, IoT sensor data, digital twin, AI-based vision, and RPA to the existing manufacturing environment to maximize data value, optimize operations, and integrate quality management It is important. This course highlights understanding and prospects for smart factories, analyzes major convergence technologies, and learns strategies and methodologies for developing various digital manufacturing systems and solutions. | |||||||||
| SFC5019 | Manufacturing Big-data Analytics | 3 | 6 | Major | Master/Doctor | Smart Factory Convergence | Korean | Yes | |
| This course deals with a broad outline of big data technologies. In order to understand the basic fundamentals of big data technologies, this course firstly introduces the state-of-the-art big data technologies which are currently being developed. In addition, the principles of HDFS, Map Reduce, and NoSQL are introduced. This course also presents the recent development trend of real-time big data processing such as Storm, Kafka, and Spark Streaming. The course has an additional focus on Machine Leaning & Data Science developed to advance data science skills that are often required to implement big data projects in manufacturing. Finally, each student designs and implement a big data system in order to resolve a given problem in manufacturing. | |||||||||
| SFC5024 | Deep Learning Technologies Application | 3 | 6 | Major | Master/Doctor | 1-4 | Smart Factory Convergence | - | No |
| This course introduces deep learning techniques and theories with an emphasis on practical application. It includes concepts and methods used to optimize highly parameterized models, the modules that make up them, and a common neural network architecture. Applications ranging from computer vision to natural language processing and decision making (reinforcement learning) are demonstrated. Through in-depth programming assignments, students learn how to implement these basic building blocks and build them using PyTorch, a popular deep learning library. In the final project, students will apply what they learn to real-world scenarios by exploring these concepts with problems they are passionate about. | |||||||||
| SPE5001 | Introduction to Energy ICT | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
| This class is to study the development of sensor network and signal processing techniques such as filtering, transformation, and feature extraction for online-monitoring and diagnosis of power plant facilities with a aid of an internet-of-things (IoT) technology. In addition, the concepts of prognostics and health management (PHM) and cyber-physical system (CPS) will be introduced, and the related hands-on practices will also be conducted. | |||||||||