Semiconductor Course List
| No. | Course Type | Course Name | Credit |
|---|---|---|---|
| 1 | Elective | Basic Mathematics and Programming Practice for Machine Learning | 3 |
| 2 | Elective | Introduction to Deep Learning | 3 |
| 3 | Elective | Introduction to Electrical and Computer Engineering | 3 |
| 4 | Elective | Introduction to Materials Science and Engineering | 3 |
| 5 | Elective | Introduction to Quantum Mechanics | 3 |
| 6 | Elective | Deep Learning | 3 |
| 7 | Elective | Industrial applications of electrical and electronic technologies | 3 |
| 8 | Elective | Topics in Semiconductor Devices | 3 |
| 9 | Elective | Multiprocessor Synchronization | 3 |
| 10 | Elective | Topics in Bioelectronics | 3 |
| 11 | Elective | Topics in Electric Energy Conversion and Circuit | 3 |
| 12 | Elective | Micro Fluid Mechanics | 3 |
| 13 | Elective | Knowledge and Database Management Systems | 3 |
| 14 | Elective | Computer Organization and Design | 3 |
| 15 | Elective | Topics in Computer and VLSI | 3 |
| 16 | Elective | Advanced Programming Methodology | 3 |
| 17 | Elective | Analog Integrated Circuits | 3 |
| 18 | Elective | Introduction to Solid State Electronics | 3 |
| 19 | Elective | Advanced Digital Integrated Circuits | 3 |
| 20 | Elective | Semiconductor Processes | 4 |
| 21 | Elective | Semiconductor Device Engineering | 3 |
| 22 | Elective | Microelectronics Fabrication | 3 |
| 23 | Elective | Nanoelectronic Devices and Quantum Transport | 3 |
| 24 | Elective | Topics in Integrated Circuit Design | 3 |
| 25 | Elective | Optimal Design of Electric Machines | 3 |
| 26 | Elective | Organic Semiconductor | 3 |
| 27 | Elective | Thin Film Devices | 3 |
| 28 | Elective | Advanced Electromagnetics 1 | 3 |
| 29 | Elective | Microwave Circuits | 3 |
| 30 | Elective | Introduction to Computer Vision | 3 |
| 31 | Elective | Micro-Electro Mechanical Systems Design & Fabrication | 3 |
| 32 | Elective | Topics in Control and Automation | 3 |
| 33 | Elective | Advanced Bioelectrical and Computer Engineering | 3 |
| 34 | Elective | Nanobiotechnology | 3 |
| 35 | Elective | Bioimaging | 3 |
| 36 | Elective | Neural Prosthesis | 3 |
| 37 | Elective | Advanced Deep Learning | 3 |
| 38 | Elective | Advanced Compilers | 3 |
| 39 | Elective | Graphics Programming | 3 |
| 40 | Elective | Embedded Systems Software | 3 |
| 41 | Elective | Topics in System Software | 3 |
| 42 | Elective | Semiconductor CEO Seminar | 3 |
| 43 | Elective | Studies in AI Semiconductor | 3 |
| 44 | Elective | Random Signal Theory | 3 |
| 45 | Elective | Topics in Electro-physics | 3 |
| 46 | Elective | Topics in AI Semiconductor | 3 |
| 47 | Elective | AI Semiconductor Device Design | 3 |
| 48 | Elective | AI Semiconductor Hardware Design | 3 |
| 49 | Elective | VLSI Design for Intelligent Systems | 3 |
| 50 | Elective | Topics in Computer Architecture | 3 |
| 51 | Elective | Advanced Operating Systems | 3 |
| 52 | Elective | Advanced Computer Architecture | 3 |
| 53 | Elective | Computer Interconnection Networks | 3 |
| 54 | Elective | Topics Intelligent Convergence Systems | 3 |
| 55 | Elective | Core Software | 3 |
| 56 | Elective | Custom LLM Accelerator Design An Algorithm-Hardware Co-Design Approach | 3 |
| 57 | Elective | Designing and Applying Autonomous AI Agents | 3 |
| 58 | Elective | Computer Architectures for Artificial Intelligence | 3 |
| 59 | Elective | A Holistic Approach to Datacenter Architecture | 3 |
| 60 | Elective | Advanced VLSI Design for Intelligent Systems | 3 |
| 61 | Elective | Digital Systems Design Methodology | 3 |
| 62 | Elective | AI Semiconductor System Design | 3 |
| 63 | Elective | Topics in Communications | 3 |
| 64 | Elective | Topics in Signal Processing | 3 |
| 65 | Elective | Recent Topics in Artificial Intelligence | 3 |
| 66 | Elective | AI Startups | 3 |
| 67 | Elective | Scalable High-Performance Computing | 3 |
| 68 | Elective | Advanced Artificial Intelligence | 3 |
| 69 | Elective | Generative Artificial Intelligence | 3 |
| 70 | Elective | Natural Language Processing | 3 |
| 71 | Elective | Machine Learning and Deep Learning for Data Science 1 | 3 |
| 72 | Elective | 3D Computer Vision | 3 |
| 73 | Elective | Reinforcement Learning | 3 |
| 74 | Elective | Pattern Recognition | 3 |
| 75 | Elective | Data Network | 3 |
| 76 | Elective | Wireless Networking | 3 |
| 77 | Elective | Optimization Theory and Applications | 3 |
| 78 | Elective | Machine Learning | 3 |
| 79 | Elective | Real-Time Systems | 3 |
| 80 | Elective | Topics in Embedded Systems | 3 |
| 81 | Elective | Topics in Information Studies | 3 |
| 82 | Elective | Machine Learning and Deep Learning for Data Science 2 | 3 |
| 83 | Elective | Semiconductor Device Physics | 3 |
| 84 | Elective | Semiconductor Lithography Technology | 3 |
| 85 | Elective | Topics in Semiconductor Materials | 3 |
| 86 | Elective | Semiconductor materials and devices for 3D integration | 3 |
| 87 | Elective | Advanced Materials for AI Semiconductor Devices | 3 |
| 88 | Elective | Principles of Material Engineering | 3 |
| 89 | Elective | Electric, Magnetic and Optical Properties of Materials | 3 |
| 90 | Elective | Integrated Circuit Processes of Semiconductor | 3 |
| 91 | Elective | Experiments in Materials 1,2 | 3 |
| 92 | Elective | Capstone Design for Material Science and Engineering | 3 |
| 93 | Elective | Self-design Experiments in Materials | 3 |
| 94 | Elective | Current Status of Electronic Materials | 3 |
| 95 | Elective | Topics in Inorganic Material and Semicondoctor Process | 3 |
| 96 | Elective | Chemical Processes in Semiconductor Fabrication | 3 |
Last Updated: July 2026
▶ Course Information
The GSSSP is a program that extends Seoul National University’s existing SSSP scholarship to international students.
To complete this program, master’s and doctoral students must fulfill the following requirement:
- Successfully complete at least 12 credits from semiconductor-related courses listed below.
Please make sure to check the updated course list every semester. Additional courses may be added upon request, subject to review.