For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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. | |||||||||
| 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. | |||||||||
| ECE5984 | Foundations of Machine Learning | 3 | 6 | Major | Master/Doctor | 1-4 | Electrical and Computer Engineering | English | Yes |
| Machine Learning is the study of how to build computer systems that learn from experience. This course will give an overview of many models and algorithms used in modern machine learning, including generalized linear models, multi-layer neural networks, support vector machines, Bayesian belief networks, clustering, and reinforcement learning. | |||||||||
| EME5172 | Advanced Dynamics | 3 | 6 | Major | Master/Doctor | 1-4 | Mechanical Engineering | English | Yes |
| The purpose and aim of this advanced dynamics course is to present fundamental theories to post graduate level students so that they attain a real comprehensive understandings about motions in 3D. An attempt will be made during the entire course to present real problem oriented material that emphasizes the ability to combine fundamental mathematics and theory of dynamics. Contents of the course may include rotational coordinates, system of particles, planar rigid body motions, and 3D rigid body dynamics. Introduction to Lagrangian and Hamiltonian mechanics will be also covered. | |||||||||
| EME5902 | Entrepreneurship Project | 1 | 2 | Major | Master/Doctor | 1-4 | Mechanical Engineering | Korean | Yes |
| This course is designed to provide how the entrepreneurship can be internalized and activated effectively. The basic concept of entrepreneurship, previous example, and business plan are studied. | |||||||||
| EME5903 | Seminar for High Technology | 1 | 6 | Major | Master/Doctor | 1-4 | Mechanical Engineering | Korean | Yes |
| Developing high technology for industrial and research fields are studied and discussed. The experts about environment technology, intelligent system, medical engineering, life science, etc. are invited to give lectures about required technology in the future. | |||||||||
| EME5904 | Special lecture by invited speaker | 1 | 6 | Major | Master/Doctor | 1-4 | Mechanical Engineering | Korean | Yes |
| The requirement and problem of the real technology in the industrial field are analyzed by inviting specialists in the field to learn the ability of solving the industrial problem. Also, management and commencement of an enterprise are studied. | |||||||||
| EME5929 | Intelligent Robotics | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | English | Yes | |
| Robotics deals with mathematical modeling, mechanics, control about the manipulation with a robot manipulator. We treat the description of orientation, coordinate transformation, forward kinematics, inverse kinematics, the relation between joint velocities and Cartesian velocities, dynamics, trajectory generation, position control, force control, and the issues of a manipulator design. | |||||||||
| EME5932 | Frontiers in Robotics | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | English | Yes | |
| The field of robotics is becoming a diverse field of research combining traditional and cutting-edge engineering knowledge. This course intends to introduce students with the basics of soft actuators, soft sensing, soft robotics, biologically-inspired robotics, biological robots, swarm robotics and other novel areas of robotics. The class will have a high focus on teamwork and the students will have to build a robot based on their interdisciplinary areas of research. | |||||||||
| EME5938 | Mechanics of Elastoplasticity | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | Korean | Yes | |
| This course covers the theory of elastoplasticity based on the continuum mechanics, and provides application examples for several materials. General stress and strain definitions are introduced for elastoplatsic range over onset of yield stress, in large deformation conditions. Students will study yield function, plastic potential, and hardening laws in order to analyze anisotropy and nonlinearity of material behaviors. Material dissipation caused by the plastic deformation is discussed with the entropy law and free energy theory. | |||||||||
| EME5940 | Introduction to Human-Robot Collaboration for AI Robot Applications | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | Korean | Yes | |
| In this class, we discuss technologies that are required for and related to human-machine, especially robot collaboration in industry and find collaboration service problems and examples. Theoretical backgrounds for human-robot collaboration, industrial process, backgrounds for artificial intelligence, and industrial safety management are discussed. Through these work, students understand the effect of human-machine(robot) collaboration in industry. | |||||||||
| EME5943 | Modern Control System | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | Korean | Yes | |
| This course is to study modern control theory for altering the dynamics of systems and managing their uncertainty. Key themes throughout the course will include linear versus nonlinear models, input/output response, system stability, state/output feedback, and robustness. This course will alow students to recognize control systems, to understand the principles of control theory, and to learn background for design and synthesis of control laws. | |||||||||
| EME5946 | Electrified Vehicle Dynamics & Control | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | Korean | Yes | |
| Interest in eco-friendly and safe future automobiles is increasing in order to overcome problems such as depletion of fossil fuels, accelerated global warming, and increase in the number of traffic accidents caused by automobiles. This course deals with the core technologies and principles of electrified vehicles driven by electric motors, one of the future vehicles represented by eco-friendly vehicles and autonomous vehicles. First, this course deals with vehicle dynamics in order to understand the dynamic characteristics of a vehicle. Then, the basic principles and control theory of hybrid and electric vehicles, which are representative electrified vehicles, are studied. Through modeling and simulation for key components, students evaluate the fuel efficiency of electrified vehicles and understand the control characteristics of electrified vehicles. | |||||||||
| EME5952 | Special Topics in Future Mobility Engineering | 3 | 6 | Major | Master/Doctor | Mechanical Engineering | Korean | Yes | |
| This course covers the global trends and research directions of future mobility, which are advancing in various domains including ground transportation, aviation, robotics, etc., with an emphasis on autonomy and eco-friendly technologies. Specifically, it delves into key technologies necessary for future vehicles, including the design, modeling, control, sensing, and AI-based intelligence technologies. | |||||||||
| ERC5005 | Machine Learning Essentials for Engineers | 3 | 6 | Major | Master/Doctor | Engineering | Korean | Yes | |
| As interest in artificial intelligence and machine learning grows, this course is designed to offer mathematical insights into machine learning techniques other than deep learning, enabling students to comprehend and effectively apply them. The course covers a range of topics including Imbalanced Learning, Bayesian Neural Networks, Monotonic Neural Networks, Neural Additive Models, Gaussian Process, Ensemble Learning, Expectation and Maximization, Neighbor Embedding, and more. This will facilitate students' understanding of machine learning-related research papers and equip them to solve real-world engineering problems in their respective fields of study. | |||||||||