DATA VISUALIZATION

데이터 시각화는 데이터를 알기 쉽게 시각화하여 연구자가 의미 있는 정보를 추출하는데 효과적인 의사 결정을 할 수 있도록 하는 유용한 분야이다. 이를 다루는 수업에서 연구 데이터 시각화 기술에 대한 적합한 선택에 초점을 맞추어 기본 기술과 개념을 소개한다. 또한 서지 및 통계 데이터를 소프트웨어 툴을 사용하여서 시각화하는 방법도 중점적으로 다룬다. 이외에도 다음과 같은 주제를 포함한다: 가) 다양한 유형의 데이터 시각화, 나) 통계 도구를 사용한 데이터 시각화, 다) 시각화 도구 및 소프트웨어, 라)서지 데이터 시각화, 라) 빅 데이터를 기반으로 한 시각화.

This course aims to introduce students to data visualization techniques and concepts using the R language. The course focuses on selecting appropriate visualization techniques for different types of data and emphasizes the effective communication of insights through visual representations. Students will gain hands-on experience with R and relevant packages to create a variety of visualizations, including bar charts, column plots, scatter plots, pie charts, heat maps, and network graphs. The course also covers customization options, data flow visualization, and techniques for presenting data effectively.

Class attendance and active participation are essential expectations for this course. It is important to note that arriving late to class and frequently leaving temporarily are not considered appropriate classroom behavior. Furthermore, if students anticipate being absent for an extended period of time due to their teaching practicum, it is important for them to contact the instructor in advance. This communication will help minimize any potential repercussions or adverse effects on their academic progress.

Grades for this course will be based on the following components: Homework Assignments: The completion and quality of programming tasks will significantly contribute to your evaluation. These assignments provide practical hands-on experience and reinforce the concepts learned in class. Dedicate sufficient time and effort to ensure their completion and strive for high-quality solutions. Examinations: Assessments will assess both theoretical knowledge and practical programming skills. They will test your understanding of key concepts, problem-solving abilities, and ability to apply programming techniques. Prepare thoroughly for these examinations to demonstrate your proficiency in programming. Class Attendance and Participation: Active engagement in class discussions and regular attendance are essential. Active participation allows for better understanding of the subject matter and provides an opportunity to clarify doubts and ask questions. Consistent attendance demonstrates your commitment to the learning process and ensures you stay up-to-date with course content. By actively participating in all components of the course, completing homework assignments with dedication, performing well in examinations, and attending classes regularly, you will have the opportunity to excel and achieve a favorable grade in this course.

This course is open to students from all majors without any specific prerequisites. It offers a comprehensive curriculum that encompasses essential knowledge and skills applicable to various academic disciplines. Regardless of your field of study, you are encouraged to enroll and actively participate in this course. The content is designed to provide a solid foundation in the subject matter and equip students with practical skills that can be applied in their respective domains.

This course enable students to leverage the power of visual representations to explore, analyze, communicate, and derive insights from data effectively. These skills are in high demand across various industries, including business analytics, data science, market research, and academia.