For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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 | |||||||||
| 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. | |||||||||
| FSI5001 | Examiner's Duty Moral | 3 | 6 | Major | Master/Doctor | - | No | ||
| Learning the duty moral to qualify as an examiner and investigator. | |||||||||
| FSI5002 | Basic Scientific Evidence | 3 | 6 | Major | Master/Doctor | - | No | ||
| A study on the basic scientific evidence through cases such as DNA analysis, handwriting analysis, fingerprint analysis, and digital forensics. We learn the standards of admission for digital evidence in this course. | |||||||||
| FSI5003 | Introduction to Scientific Investigation | 3 | 6 | Major | Master/Doctor | - | No | ||
| The method of collecting evidence on the spot, the territory of forensic science such as DNA, bloodstain pattern analysis, fingerprint, footprint, digital information, and their admissibility of evidence in court will be learned. | |||||||||
| FSI5007 | Deoxyribonucleic Acid for Forensics | 3 | 6 | Major | Master/Doctor | - | No | ||
| This lecture/discussion course will focus on how DNA is used in forensics. The subjects we will deal with are (1) The role of DNA in cells, (2) The importance of DNA in forensics, (3) The techniques of isolating DNA for forensics, (4) What kind of molecular methods are available for forensics, (5) The rationales to use these methods in forensics, (6) How to apply these methods in forensics. | |||||||||
| FSI5009 | Analytical Chemistry for Forensics | 3 | 6 | Major | Master/Doctor | - | No | ||
| Forensic analyst should have fundamental knowledge and skill in chemical analysis. In this class Instrumental analysis will be discussed, because most of chemical analyses are carried by using chemical instruments. Spectroscopic analyses and separation analyses are covered in this class to make student can use their knowledge and skill directly at the field. Fundamentals of spectroscopic analysis, UV/Visible method, Fluorescence method, Infrared method, Raman analysis, Mass spectrometry, Intoduction to Separation, Gas chromatography, High performance liquid chromatography and their applications will be discussed with students. | |||||||||
| FSI5013 | Criminal Procedure Law | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| Understanding due process by comprehending criminal case management procedure including investigation, prosecution, and evidence examination. | |||||||||
| FSI5018 | Introduction to Legal Medicine | 3 | 6 | Major | Master/Doctor | - | No | ||
| Legal medicine can be defined as the application of knowledge from medicine and science to problem solving in the field of law that contribute to the protection of human rights. Legal medicine can be divided into forensic pathology and medical jurisprudence. Forensic pathology represents the determination of the cause and manner of sudden, unexpected, and violent deaths. Medical jurisprudence is concerned with a broad range of medical, legal, and ethical issues, as well as human rights and rights of individuals. In this lecture will mainly deal with forensic pathology. 1. Describe the definition of death, and explain the cause and manner of death. 2. Describe the postmortem changes and estimation of postmortem interval. 3. Describe the definition and classification of injury. 4. Describe the process and characteristic of injuries by traffic accidents. 5. Understand the findings of asphyxia and explain the classification. 6. Explain about drowning, poisoning and the death by fire. 7. Identify the general findings of sudden unexpected natural death. | |||||||||
| FSI5020 | IT Law | 3 | 6 | Major | Master/Doctor | - | No | ||
| Study on Law and Code such as Constitution Law, Administrative Law, Adjective Law, Criminal Law, Privacy Protection Act, Protection of Communication Secrets Act, Act on the Protection of Information and Communications Infrastructure in Korean Legal System and learn the relevant facts between the Laws and Information Technology(IT). | |||||||||
| FSI5021 | Cyber Crime and Response | 3 | 6 | Major | Master/Doctor | - | No | ||
| Study on various types of cyber crime such as hacking crime related backing and personal information, computer virus, malicious code, cyber terror, cyber bullying, cyber sexual harassment etc. Through studying the cyber crimes, we also establish the origin of the crimes and cope with them. | |||||||||
| FSI5024 | E-Discovery | 3 | 6 | Major | Master/Doctor | - | No | ||
| In the United States, the E-discovery system has been introduced since 2008 by amending the Criminal Procedure Act. In E-discovery, before the formal trial, the civil proceedings at the stage of trial preparation commence at the same time the evidence that the plaintiff and the defendant have, the criminal trial is the test and the defendant (counsel) It is a system that makes it impossible to use in principle in court. The United States is evolving to find evidence in files or emails through this E-discovery scheme. E-discovery is expected to be introduced in the future, so research and attention should be paid to E-discovery. | |||||||||
| FSI5025 | Civil Procedure and Evidence Law | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course is designed to provide students with an understanding of the basic procedures of civil litigation, the principles of civil litigation, and the evidence law for establishing facts through investigation of evidence and to help their deepening studies for the evidence law. | |||||||||
| FSI5026 | Internships | 2 | 4 | Major | Master/Doctor | - | No | ||
| In addition to the theory of scientific investigation, students are expected to experience the necessary field work directly at each institution. | |||||||||