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Academic Programs

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Department of Electrical and Computer Engineering

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

교육과정
Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
AIM4001 Advanced Big Data Analytics 3 6 Major Bachelor/Master Artificial Intelligence - No
This course introduces fundamental data mining and machine learning techniques for big data analytics. The emphasis in the course will be learning key techniques that are required to extract meaningful information from big data, and developing scalable data mining algorithms for big data analytics. The first half of the course will cover various supervised and unsupervised machine learning methods (theoretical analysis of the methods and their practical applications), and the last half of the course will focus on scalable graph mining techniques with special emphasis on analyzing large-scale social networks. There will be one midterm, three assignments, and the final project where students will be expected to develop scalable algorithms for collecting and analyzing big data.
AIM5001 Theories of Artificial Intelligence 3 6 Major Master/Doctor Artificial Intelligence Korean Yes
In this course students will learn the fundamental algorithms of Aritificial Intelligence including the problem solving techniques, search algorithms, logical agents, knowledge representation, inference, and planning. After taking the course, students are expected to implement the algorithms using computer programming languages.
AIM5004 Deep Neural Networks 3 6 Major Master/Doctor Artificial Intelligence - No
In this class, we will cover the following state-of-the-art deep learning techniques such as linear classification, feedforward deep neural networks (DNNs), various regularization and optimization for DNNs, convolutional neural networks (CNNs), recurrent neural networks (RNN), attention mechanism, generative deep models (VAE, GAN), visualization and explanation.
AIM5025 Intelligent Robot and System 3 6 Major Master/Doctor 1-4 Artificial Intelligence - No
Inordertouserobotsveryefficiently,robotsarerequestedtobeabletoperformalltasksashumanscan.Thiscoursediscussesthetechniqueofsensoranditsapplicationinordertomakerobotsperformtasksintelligently.
AIM5026 Introduction to Robotic Intelligence 3 6 Major Master/Doctor Artificial Intelligence - No
Robot is defined as an intelligent system connecting sensors and actuators. As an intelligent system, robot is to play a key role for providing necessary services to human by automatically carrying out tasks requiring navigation and manipulation. To this end, robot needs to recognize objects and understand surroundings while reasoning and planning the behaviors necessary for carrying out tasks. Especially, it is essential for robot to be able to obtain its capabilities of recognition and understanding of environments as well as of reasoning and planning of behaviors by learning. This course deals with the fundamentals of robot intelligence on how robot learns for the recognition and understanding of environments as well as for the reasoning and planning of behaviors associated with manipulation and navigation.
AIM5064 Special topics in visual computing 3 6 Major Master/Doctor 1-4 Artificial Intelligence Korean Yes
This is a graduate seminar course in visual computing. We will survey and discuss the recent research papers in computer vision area, such as image recogniaion, reconstruction, 3D vision, simulation, generative models, etc. Throughout this course, students get familiar with the recent innovations in computer vision area and identify open questions and new research directions in this field.
AIM5065 OPEN AI NETWORKING 3 6 Major Master/Doctor 1-4 Artificial Intelligence English Yes
Mobile/wireless networks are going through a new AI revolution triggered by the challenges of hyper-connectivity, hyper-low latency communication, and massive data orchestration for enormous connected objects. As such, they are one of the most active research areas in Beyond 5G and 6G in terms of growth and innovation. The “AI and 5G/6G” course covers basic knowledge of 5G/6G mobile networks and available AI technologies for improved network performance and efficient management of resources. In particular, the course is split in three parts, where the first part discusses basic 5G architecture and new technologies that are shaping 6G architecture, such as cloud-native computing, AI-native communication, and deterministic networking. Second part covers the state-of-the-art Deep Learning (DL) approaches that are relevant for 5G/6G mobile networks, like recurrent models, generative adversarial networks, transformer networks, and deep reinforcement learning. Third part presents the latest case studies of AI based dynamic orchestration of network behavior by using parameters like traffic variation, localization, mobility, and user context. At the end of the course, the student will have a comprehensive vision of 5G/6G mobile networks and relevant state-of-the-art AI technologies that open up numerous industrial, management, and research opportunities.
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.
DIM5023 Entertainment recommendation system 1 3 6 Major Master/Doctor Immersive Media Engineering Korean Yes
This course starts from the most basic concepts of recommendation systems, prioritizes theoretical understanding of the latest theories, and conducts practical projects to implement them by applying them to entertainment datasets, so it aims to understand and learn recommendation systems from introduction to application. In particular, it is designed to be a major course for master's/doctoral students, and students will select textbooks on related topics and learn each chapter on their own, and through the process of transferring knowledge to other students, they will go through a process of proactive knowledge acquisition, and the instructor will increase the effectiveness of learning through important questions and answers during this process. In addition, we plan to invite field developers with relevant experience in the field to listen to the latest trends related to the topic and ask questions.
DMC5007 On-device Deep Learning 3 6 Major Master/Doctor 1-4 Digital Media Communication - No
This course pursues in-depth study on deep neural network (DNN) compression techniques for on-device deep learning, which allows smartpones and IoT devices to execute DNN applications. The detailed topics include DNN pruning, low-precision bit quantization, and neural network architecture search (NAS).
ECE4223 Semiconductor Process Technology 3 6 Major Bachelor/Master 1-4 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.
ECE4233 Simulation Engineering of Electric Power Systems 3 6 Major Bachelor/Master 1-4 - No
The objective of this lecture is to present methods of power system simulation, particularly with the aid of a personal computer, in sufficient depth to give the student the basic technique at the graduate level. Main subjects are steady-state & transient power system simulation, fault modeling technique, FACT(flexible alternating current transmission) simulation and the usage of EMTP, ATP, PSCAD/EMTDC.
ECE4237 Robotics 3 6 Major Bachelor/Master 1-4 - No
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 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.
ECE4245 Automation and Design of Electric Power System 3 6 Major Bachelor/Master 1-4 Korean Yes
In many coutries, the electric supply industry is undergoing a significant restructuring that has only just begun. Fully competitive markets of electric energy are fairly recent phenomena, and the existing competitive markets have not experienced significant of resource shortages yet. This course deals with the basic principles of power system automation from the point view of the central control facilities under competitive environment. And it discusses central computers used to process power system economic operating data, present vital data to an operator, and allow the operator to implement commands to equipment field. Also it contains the economic load dispatch, the Gauss-Seidel, Newton-Raphson, and decoupled method to iteratively calculate network power flow.