Inspiring Future, Grand Challenge

Search
Close
search
 

Undergraduate

  • home
  • Undergraduate
  • Child Psychology and Education
  • Course & Curriculum

Course & Curriculum

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
CHS2001 New humanity Phono Sapiens created by Smartphone 1 2 Major Bachelor 1-4 Challenge Semester - No
The humanity which have begun using smartphones are showing changes in consumer psychology, consumer behavior and market ecosystems due to rapidly changing lifestyles. This is Phono Sapiens, the new humanity is the hero of the revolution. The purpose of this course learn about the changes in business models due to the development of big data, artificial intelligence, and digital platforms by the change of consumption civilization. And it analyzes the development direction of continuously developing 5G, Internet of Things, robot, drone, autonomous vehicle, and smart factory. On this basis, companies present and understand new business innovation and directionality of change for new consumers called phono sapiens
CHS2002 Data Science and Social Analytics 1 2 Major Bachelor 1-4 Challenge Semester - No
This course is intended to examine human behaviors and social phenomena through the lens of data science. Students also may learn online data collection and analysis in social media spaces. It deals with both theory and practice, but relative portion may change in each semester without prior notice.
CHS2013 The Convergence of Cognitive Neuroscience and Neurotechnology with Humanities and Social Sciences 3 6 Major Bachelor 1-4 Challenge Semester - No
This course will introduce fundamentals of how human brain works and the state-of-the-art of neuroscience research. This course will cover the convergence of cognitive neuroscience and neurotechnology with humanities and social sciences (e.g., brain-computer interface, neuroscience-based cognitive computing, neuroergonomics, etc.), their applications and future directions through class discussions. This course aims for students to 1) understand the literature in the fields of cognitive neuroscience and neurotechnology based on the understanding of humanities and social sciences; 2) articulate the domains and contexts in which cognitive neuroscience and neurotechnology may be effective; 3) develop an ability to lay out the open questions and address challenges in cognitive neuroscience and neurotechnology research today; and 4) prepare them to be more knowledgeable and proficient professionals.
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
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
CHS7004 Thesis writing in humanities and social sciences using Python 3 6 Major Bachelor/Master/Doctor Challenge Semester Korean Yes
This course is to write a thesis in humanities and social science field using Python. This course is for writing thesis using big data for research in the humanities and social sciences. Basically, students will learn how to write a thesis, and implement a program in Python as a research methodology for thesis. Students will learn how to write thesis using Python, which is the most suitable for processing humanities and social science related materials among programming languages ​​and has excellent data visualization. Basic research methodology for thesis writing will be covered first as theoretical lectures. Methodology for selection of topics will be discussed also. Once a topic is selected, a lecture on how to organize related research will be conducted. In the next step, students learn how to write necessary content according to the research methodology. Then how to suggest further discussion along with how to organize bibliography to complete a theoretical approach. The basic Python grammar is covered for data analysis using Python, and the process for input data processing is conducted. After learning how to install and use the required Python package in each research field, the actual data processing will be practiced. To prepare for the joint research, learn how to use the jupyter notebook as the basic environment. Learn how to use matplolib for data visualization and how to use pandas for big data processing.
CHS7004 Thesis writing in humanities and social sciences using Python 3 6 Major Bachelor/Master/Doctor Challenge Semester Korean Yes
This course is to write a thesis in humanities and social science field using Python. This course is for writing thesis using big data for research in the humanities and social sciences. Basically, students will learn how to write a thesis, and implement a program in Python as a research methodology for thesis. Students will learn how to write thesis using Python, which is the most suitable for processing humanities and social science related materials among programming languages ​​and has excellent data visualization. Basic research methodology for thesis writing will be covered first as theoretical lectures. Methodology for selection of topics will be discussed also. Once a topic is selected, a lecture on how to organize related research will be conducted. In the next step, students learn how to write necessary content according to the research methodology. Then how to suggest further discussion along with how to organize bibliography to complete a theoretical approach. The basic Python grammar is covered for data analysis using Python, and the process for input data processing is conducted. After learning how to install and use the required Python package in each research field, the actual data processing will be practiced. To prepare for the joint research, learn how to use the jupyter notebook as the basic environment. Learn how to use matplolib for data visualization and how to use pandas for big data processing.
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.
DAI5001 Fundamentals of Artificial Intelligence 3 6 Major Master/Doctor 1-8 Applied Artificial Intelligence - No
Artificial intelligence is a field of research into information processing models that can mimic human intelligence and cognitive functions. As a fundamental problem of artificial intelligence, it deals with theories and fundamental computational problems on the methods of empirical exploration, reasoning, learning and knowledge expression. It deals with logic-based proof of theorem, game theory, intelligent agent, etc., learns the basic principles of neural network, evolutionary computation, and beigean network, and examines areas such as expert system, computer vision, natural language processing, data mining, information search and bioinformatics as examples of its application.
EDU3039 Understanding E-Learning 3 6 Major Bachelor Education - No
The purpose of this course is to provide an opportunity for students to learn about recent trends, theories, design principles, and issues regarding eleanring and online education. Students will acquire knowledge about the design and development of elearning based on what they learn from cases and previous studies. As a group, students work with clients including teachers, professors, HR personnels, or online course developers, and consultants or instructional designers in higher education. Based on technology consultation results, students will write a report and decisions make as a learnaing technologist. In addition, students provide solutions or suggestions to the clients about how to improve teaching and learning using learning technologies. If necessary, students are expected to demonstrate an example of learning technology integration in teaching and learning.
EDU5086 Analysis of Factors 3 8 Major Master/Doctor 1-4 Education - No
The purpose of this course is to enable an investigator to properly utilize factor analysis as a research tool. Such utilization requires an understanding of when the differences in possible mathematical procedures may have a major impact upon the substantive conclusions and when the differences might not be relevant for a given research study. So, This course has stress on the mathematical foundations of factor analysis.
ERP4001 Creative Group Study 3 6 Major Bachelor/Master - No
This course cultivates and supports research partnerships between our undergraduates and faculty. It offers the chance to work on cutting edge research—whether you join established research projects or pursue your own ideas. Undergraduates participate in each phase of standard research activity: developing research plans, writing proposals, conducting research, analyzing data and presenting research results in oral and written form. Projects can last for an entire semester, and many continue for a year or more. SKKU students use their CGS(Creative Group Study) experiences to become familiar with the faculty, learn about potential majors, and investigate areas of interest. They gain practical skills and knowledge they eventually apply to careers after graduation or as graduate students.
GSP5241 Spatial Modeling for Social Science Research 3 6 Major Master/Doctor Public Administration - No
Spatial dependence is prevalent in the society. Geographically proximate individuals, groups, and localities have similar characteristics and behave similarly via spillover effect. Also, the local governments that are closely located often pursue similar policy directions as they are affected by each other. This class aims to explore how to apply spatial dependence in social science research. The class topics include the concept and origin of spatial dependence, global/local spatial analysis, visualization of spatial dependence, and various spatial regression models such as spatial lag, spatial error, geographically weighted regression, and spatial Durbin.
HRD5011 Picturebooks and Play 3 6 Major Master/Doctor 1-4 Human Resource Development - No
Modern picture books have developed as an unique art form rather than a sub genre of children's literature. This course will examine the relationships among picture books, imagination and play through literary works. Play elements of picture book reading behavior of child and adult readers will be observed and analyzed. The topics that this course will deal with are play and art, play and imagination, children's play expressed in picture books, child psychology, play elements of picture books and picture book reading.
HRD5012 Media in the Life and Education of Children 3 6 Major Master/Doctor 1-4 Human Resource Development - No
The purpose of this course is to explore the role of mass media in children's lives and education. The focus will be on the way to help children to grow as responsive readers of mass media. The topics include: the change in views on child in past and present; the trend and features of children's use of media in our society; the types and development of media education programs.