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Department of Semiconductor Systems Engineering

For more details on the courses, please refer to the Course Catalog

Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
CHS2003 Robust System Design with Big Data Analytics and Artificial Intelligence 2 4 Major Bachelor 1-4 Challenge Semester Korean Yes
In this course, the fundamental theories and methodologies on big-data analytics and artificial intelligence (AI) algorithms for prognostics and health management (PHM) of engineering systems are mainly covered. More specifically, the reliability analysis, sensor-based big-data collection, signal processing, statistical feature extraction and selection, and AI-based modeling are studied, and the hands-on practices are also carried out. In addition, various case examples are introduced to study the robust engineering system design using the big-data analytics and AI algorithms.
CHS2012 IoT Project 2 4 Major Bachelor 1-4 Challenge Semester - No
It is a course for students who are not familiar with software and hardware, but who are interested in Internet of Things area. It aims to provide easy and convenient steps of the area, including education of C language basics and various digital/analog sensor control conducted with a toolkit such as Arduino. Communication skills and cooperative spirit can be obtained by carrying out IoT projects through group activities.
CHS7002 Machine Learning and Deep Learning 3 6 Major Bachelor/Master/Doctor Challenge Semester - No
This course covers the basic machine learning algorithms and practices. The algorithms in the lectures include linear classification, linear regression, decision trees, support vector machines, multilayer perceptrons, and convolutional neural networks, and related python pratices are also provided. It is expected for students to have basic knowledge on calculus, linear algebra, probability and statistics, and python literacy.
CHS7003 Artificial Intelligence Application 3 6 Major Bachelor/Master/Doctor Challenge Semester - No
Cs231n, an open course at Stanford University, is one of the most popular open courses on image recognition and deep learning. This class uses the MOOC content which is cs231n of Stanford University with a flipped class way.  This class requires basic undergraduate knowledge of mathematics (linear algebra, calculus, probability/statistics) and basic Python-based coding skills. The specific progress and activities of the class are as follows. 1) Listening to On-line Lectures (led by learners) 2) On-line lecture (English) Organize individual notes about what you listen to 3) On-line lecture (English) QnA discussion about what was listened to (learned by the learner) 4) QnA-based Instructor-led Off-line Lecture (Korean) Lecturer 5) Team Supplementary Presentation (Learner-led)   For each topic, learn using the above mentioned steps from 1) to 5). The grades are absolute based on each activity, assignment, midterm exam and final project.   Class contents are as follows. - Introduction Image Classification Loss Function & Optimization (Assignment # 1) - Introduction to Neural Networks - Convolutional Neural Networks (Assignment # 2) - Training Neural Networks - Deep Learning Hardware and Software - CNN Architectures-Recurrent Neural Networks (Assignment # 3) - Detection and Segmentation - Generative Models - Visualizing and Understanding - Deep Reinforcement Learning - Final Project.   This class will cover the deep learning method related to image recognitio
COV3002 Ubiquitous Society and Communication Competency 3 6 Major Bachelor 3-4 SKKU Institute for Convergence Korean,Korean Yes
This course generally focuses on understanding the characteristics of ubiquitous society and also it focuses on developing a new communication skill which is demanded by society. Media revolution called 'Media2.0' brought about at large reform of the society, it has a significant influence on society. Eventually the course examines those changes and evolutions in our society and also what they really are. The course deals with understanding the digital technology and the ethical issues behind the digital technology as well. A discussion on media ecosystem will suggest a new level of social meaning of Communication.
DES4001 Convergence Capstone Design 3 6 Major Bachelor/Master Design Korean Yes
Various students from different majors, Design, Art, IT, Business, Engineering, and etc., are gathered to study the development of future new technology, services and creative design products. Also, they are processing the prototype of the study and supporting the application of effective ideas. The purposes of this study are to overcome the present level of studies' approaches and create new and innovative values and to acquire creativeness, Problem Based Learning skill, and ability to conduct Team Project.
EAM4014 Global Techno Management 2 4 Major Bachelor/Master 1-4 Advanced Materials Science and Engineering - No
The requirement and problem of the real technology in the industrial field are analyzed by inviting specialists and CEOs to learn the ability of solving the industrial problem. Also, management and commencement of an enterprise are studied.
ECE4223 Semiconductor Process Technology 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering English Yes
This course helps to understand the overall semiconductor processes by introducing the theory and the application of unit processes; photolithography, photo-mask, dry-etch, cleaning, chemical-mechanical polishing(CMP), diffusion and thin film, and module processes; transistor, isolation, capacitor, interconnection. This also suggests the direction of process technologies for the future generations.
ECE4237 Robotics 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering Korean Yes
This course discusses the kinematics and the dynamics of manipulators. The path planning of each joint and some control algorithms of manipulators are also discussed.
ECE4238 Linear Systems 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering English Yes
Methods of analysis for continuous and discrete-time linear systems. Convolution, classical solution of dynamic equations, transforms and matrices are reviewed. Emphasis is on the concept of state space. Linear spaces, concept of state, modes, controllability, observability, state transition matrix, state variable feedback, compensation, decoupling are treated.
ECE4246 Digital Control 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering - No
Many industrial control systems include digital computers as an integral part of their operation. Recent trends toward digital control of dynamic systems, rather than analog control, is mainly due to the recent revolutionary advances in digital computers and to advantages found in working with digital signals rather than continuous-time signals. Also, the availability of low-cost microprocessors and microcomputers established a new trend for even small-scale control systems to include digital computers to obtain optimal performance. The main purpose of this course is to present a comprehensive treatment of the analysis and design of discrete-time control systems. In particular, this course provides clear and easy-to-understand explanations for concepts involved in the study of discre-time control systems.
ECE4249 Computer Vision 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering Korean Yes
This course focuses in the study of theories for image analysis. The first part consists of Image formulation model, early processing, boundary detection, region growing and segmentation, motion detection, merging and introduction of morphology. The second part, we cover basic concepts of statistical model, dis- criminant function, decision boundary and rules and neural network for visual pattern recognition.
ECE4258 Advanced Systems Programming 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering - No
This course introduces the system programming technologies that uses the system call interfaces of the Unix/Linux operating systems. In detail, we study the system programming methodologies that deals with files and file systems, processes, IPC(Inter-Process Communication) facilities, signals, and I/O management components.
ECE4260 Design Pattern 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering - No
This course intends to provide techniques about design patten and refactoring. The former is about patternized design knowledge of expert designers, that is particulary important to improve software quality. The latter is an advanced technique to improve software design without changing internal structure of the software. This course is a prerequisite for SCM certification of MIC.
ECE4261 Nano Device 3 6 Major Bachelor/Master 1-4 Electrical and Computer Engineering English Yes
In this course, we will cover many topics including the growth methods and the physical/electrical characteristic for sub-nanometer dimensional materials. With the basic knowledge on nano scale materials, we deal with the nano devices (e.g., memory, logic, display devices, etc.), nano structures and operation principles.