For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| PSE5017 | Building Integrated PhotoVoltaics(BIPV) Practical Working Internship2 | 3 | 6 | Major | Master/Doctor | Photovoltaic System Engineering | - | No | |
| This is a advanced hands-on training course in the field of building photovoltaics, providing students with the opportunity to apply the knowledge gained in BIPV-related coursework to actual industrial sites. Students visit actual companies or institutions in the field of building-based photovoltaics to learn and practice BIPV-related research/process equipment and advanced business processes. In particular, the course reflects the convergence of the fields of architecture and electricity, considering not only existing photovoltaic modules but also the specificity of building materials. The learning process is conducted with experts and the final evaluation is also conducted with the experts in the field. | |||||||||
| PSE7001 | Electronic Thin Film Process | 3 | 6 | Major | Bachelor/Master/Doctor | Photovoltaic System Engineering | Korean | Yes | |
| The content covers various material manufacturing technologies for electronic materials used in semiconductor displays, such as evaporation, sputtering, PECVD, PEALD, and their fundamental technologies, including plasma technology and vacuum technology. The study includes the mechanical, physical, electrical, and chemical properties of the manufactured materials, as well as methods for measuring these properties. These technologies cover essential aspects from the fundamentals to specialized techniques for manufacturing semiconductor and display materials. The content is designed to help undergraduate and graduate students who aspire to work in component, material, equipment, and component companies related to semiconductors and displays. It aims to provide them with key skills, especially for those researching thin film materials for various semiconductor and display applications. | |||||||||
| ROB7001 | principles of deep learning | 3 | 6 | Major | Bachelor/Master/Doctor | 1-8 | Intelligent Robotics | - | No |
| This course is about deep learning, which forms a major axis of modern artificial intelligence systems. Learning the Multilayer Perceptron (MLP) structure based on basic linear model machine learning methodologies; learning methodologies for deep neural networks through gradient descent; various optimization methodologies; learning about the structure and theory of Convolutional Neural Networks (CNN), and their various applications; learning about the structure and theory of Recurrent Neural Networks (RNN), and their various applications; learning the structure, theory, and applications of Transformers; basics of generative models; basics of multimodal learning | |||||||||
| SEE4001 | Special topics in semiconductor devices and processing | 3 | 6 | Major | Bachelor/Master | 1-4 | Semiconductor Convergence Engineering | Korean | Yes |
| On-site processing required for semiconductor device manufacturing experts give lectures directly so that students acquire the knowledge they need in the field. Additionally, through this lecture, students understand the physical operating principles and structure of manufacturing equipment. As semiconductor devices become highly integrated, we look at recent process and equipment development trends and problems with current processes that have become issues. | |||||||||
| SEE4003 | AI Semiconductor Device Simulation | 3 | 6 | Major | Bachelor/Master | 1-4 | Semiconductor Convergence Engineering | Korean | Yes |
| We introduce the latest semiconductor technologies such as ultra-low power logic operation and multi-function memory operation, which are the characteristics required for semiconductors to run artificial intelligence algorithms, and optimize semiconductor technology through actual simulation based on our understanding of these. The electrical characteristics of 3D semiconductor devices due to semiconductor device scaling, ultra-low power semiconductor devices due to new charge transport mechanisms, and memory devices based on various new devices are confirmed through actual simulation exercises and optimized and adjusted by adjusting device design parameters. Check the impact on the operation of the artificial intelligence algorithm. Through this course, you can develop an understanding of the latest semiconductor device theory, especially artificial intelligence semiconductor device theory, and develop not only theory but also basic practical skills by selecting practical topics that can be frequently experienced in the actual industry and carrying out projects. There is a purpose. Prerequisite courses include physical electronics, semiconductor engineering, semiconductor device design, and electronic circuits. | |||||||||
| SUP5002 | Computer Architecture and Its Applications to Artificial Intelligence | 3 | 6 | Major | Master/Doctor | 1-4 | Superintelligence Engineering | - | No |
| This course focuses on principles and mechanisms related to the modern computer architecture including numerical representation, arithmetic operations, datapath and pipelining, cache hierarchies, memory systems, storage and I/O systems. As an application of computer architecture, this course also covers recent HW architectures and techniques for efficient training and inference of AI (especially deep learning) models. | |||||||||
| SUP5009 | Bioelectronic Devices and Intelligent Information Processing | 3 | 6 | Major | Master/Doctor | 1-2 | Superintelligence Engineering | Korean | Yes |
| The course covers the flexible electronic/bioelectronic materials and functional devices. Furthermore, various fabrication methods and characteristic analyses regarding soft electrodes, sensors, and non-volatile memories will be addressed. In addition, this course covers diverse artificial intelligence applications for effectively achieving high-fidelity physiological signals and biomedical images. For example, one topic is to discuss recent progress and limitation of sensors, memory devices, and artificial intelligence and predict their future prospects. The one goal of the course is to develop the ability of solving issues via various engineering aspects. | |||||||||
| WIS5059 | Wired-and-Wireless Communications and Computer | 3 | 6 | Major | Master/Doctor | 1-4 | Interaction Science | - | No |
| The goal of this course is to provide IS(Interaction Science) graduate students with the knowledge about wired-and-wireless communications that are used by computers and mobile computing devices (e.g., Smartphones, Tablets, and Laptops) for various services through cloud. This course decomposes the Internet technology (as the core of computer networks) into multiple layers and explains protocols required for those layers. That is, based on the OSI (Open Systems Interconnection) model, this course divides the Internet architecture into Physical layer, Data link layer, Network layer, Transport layer, and Application layer and then articulates the protocols necessary for running services in each layer. This course is designed to deliver lectures with 9 topics as follows. 1. Computer Networks and the Internet 2. Application Layer 3. Transport Layer 4. The Network Layer 5. The Link Layer and Local Area Networks 6. Wireless and Mobile Networks 7. Multimedia Networking 8. Security in Computer Networks 9. Network Management | |||||||||