For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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. | |||||||||
| 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. | |||||||||
| SEE5002 | Semiconductor Device Principles | 3 | 6 | Major | Master/Doctor | 1-4 | Semiconductor Convergence Engineering | Korean | Yes |
| Semiconductor products built in for automation and intelligence of electronics are manufactured by connecting and integrating up to 10 billion unit devices (MOSFETs, BJTs) with each other, and characteristics such as final performance and power consumption depend heavily on the characteristics of the unit device. In this course, we want to provide theoretical knowledge on the development of semiconductor manufacturing processes through the physical understanding of these unit elements. | |||||||||
| SEE5005 | Introduction to Semiconductor Engineering | 3 | 6 | Major | Master/Doctor | 1-4 | Semiconductor Convergence Engineering | Korean | Yes |
| This subject includes general content required for the semiconductor industry. It covers software/architecture, materials/parts/equipment, devices, and design. Ultimately, the goal is to increase understanding of all semiconductor-related industries. Professors specializing in three fields take turns giving lectures. | |||||||||
| SEE5008 | Flexible electronic device engineering | 3 | 6 | Major | Master/Doctor | 1-4 | Semiconductor Convergence Engineering | Korean | Yes |
| Flexible electronic devices, utilizing micro/nanomaterials and structures, have garnered significant attention across various application fields due to the high-performance electrical and mechanical characteristics of flexible electronics. This course provides an overview and introduction to diverse application areas of flexible electronic devices. It covers overall content from micro/nanomaterials and structure fabrication methods based on the semiconductor manufacturing process to the integrated electrical systems for flexible electronics. Each detailed topic introduces 1. Electrical/mechanical properties of flexible electronic materials, 2. Fabrication method for micro/nanostructures, 3. Electrical/mechanical properties of micro/nanostructures, 4. Integrated electrical system of flexible electronics and applications. Throughout the course, we will engage in discussions on a variety of cutting-edge research activities. | |||||||||
| 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 | |||||||||