For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ISS3222 | Introduction to Machine Learning | 3 | 6 | Major | Bachelor | English | Yes | ||
| Covers fundamental concepts for intelligent systems that autonomously learn to perform a task and improve with experience, including problem formulations (e.g., selecting input features and outputs) and learning frameworks (e.g., supervised vs. unsupervised), standard models, methods, computational tools, algorithms and modern techniques, as well as methodologies to evaluate learning ability and to automatically select optimal models. Applications to areas such as computer vision (e.g., characte r and digit recognition), natural language processing (e.g., spam filtering) and robotics (e.g., navigating complex environments) will motivate the coursework and material. | |||||||||
| ISS3224 | Data Visualization | 3 | 6 | Major | Bachelor | English | Yes | ||
| This course explores the field of data visualization. Topics cover the expanse of visualization from data preparation and cleaning to visualization types such as time series, box plots, and violin plots. Included in our study are visualization tools, online interactive visualizations, and other issues related to the display of big data. | |||||||||
| ISS3233 | Statistics in Python | 3 | 6 | Major | Bachelor | 1-4 | English | Yes | |
| This course will cover elementary topics in statistics using Python. The statistics topics include principles of sampling, descriptive statistics, binomial and normal distributions, sampling distributions, point and confidence interval estimation, hypothesis testing, two sample inference, linear regression, and categorical data analysis. Using Python, students will learn basic knowledge in Python programming, data management, data formats and types, statistical graphics and exploratory data analysis, and basic functions for statistical modeling and inference. | |||||||||
| ISS3266 | Digital Strategies in Media and Communication | 3 | 6 | Major | Bachelor | 1-4 | English | Yes | |
| This course presents a clear overview of the digital media strategies for business and offers opportunities for acquiring analytical skills of performing integrated strategic communication (ISC) functions in digital environments. Topics coveredinclude search engine optimization, pay-per-click advertising, email marketing, big data, digital/social media analytics, social media management, content strategies, and mobile marketing. Through online module sessions, class assignments, discussions, andsimulation project, students will be able to implement an integrated digital media campaign. Attention will also be given to working knowledge of the digital analytics tools for creating, managing, executing, and evaluating digital strategies | |||||||||
| ISS3290 | Introduction to Big Data Analysis | 3 | 6 | Major | Bachelor | English | Yes | ||
| Understand the genesis of Big Data Systems • Understand practical knowledge of Big Data Analysis using Hive, Pig, Sqoop • Provide the student with a detailed understanding of effective behavioral and technical techniques in Cloud Computing on Big Data • Demonstrate knowledge of Big Data in industry and its Architecture • Learn data analysis, modeling and visualization in Big Data systems | |||||||||
| LIS2001 | Introduction to Library and Information Science | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Discussion of the theory and evolution of the modern library, of the informationgeneration, selection, organization, storage, retrieval and of the cultural fun-ctions and social roles of the information centers. | |||||||||
| LIS2004 | Library and Information Center Management | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Discussion of the general theory and techniques in the library and information management, including staff, facilites, budgets and activities. | |||||||||
| LIS2005 | Introduction to Information Science | 3 | 6 | Major | Bachelor | 2-3 | - | No | |
| Generation, recording, production, transmission, processing and use of informaiton ; information representations ; efficient processing devices. | |||||||||
| LIS2007 | Information Retrieval | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| This course introduces concepts and principles relevant to information storage, classification and indexing, and retrieval. | |||||||||
| LIS2008 | Information Behavior | 3 | 6 | Major | Bachelor | 2-3 | - | No | |
| This course provides cognitive and psychological theories and approaches to understanding human information behaviors. It examines techiques to apply theories for developing information services and systems. | |||||||||
| LIS2012 | Introduction to Bibliography | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Discussion of the nature of bibligraphy as a discipline, technique of analytica-l, descriptive, and enumerative bibliography, and bibliographical organization and control. | |||||||||
| LIS2013 | Classical Materials Organization I | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Comprehensive overview of the classical materials written in chinese.? This seminar will help students improve the ability of interpretation and practical application of classics. | |||||||||
| LIS2014 | Information Literacy | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| To improve of understandig about what information need is, what information literacy is, how to cope and keep up with the information age, and advanced methods of information literacy which can be used in school and college Libaries. | |||||||||
| LIS2015 | Principles of Metadata | 3 | 6 | Major | Bachelor | 2-3 | - | No | |
| This course introduces students to the systematics of knowledge organization and data semantics. This course also covers the practical understanding of metadata standards for various domains, issues in metadata interoperability. It examines international standards, activities, and projects, including trends and practices in linked data-enabled metadata encoding. On completion of this course students will be able to understand the principles, concepts and types of metadata explore various metadata standards in specific domains understand different issues in the applications of metadata standards in a larger context of a project, a community, and the society understand different issues in the metatada interoperability understand the ISO/IEC 11179 MDR explore various building practices of metadata registry | |||||||||
| LIS2016 | Introduction to Information Classification | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| The purpose if the course is to enable the student to understand the problems and prospects of bibliographic and information classification, to familiarize the student with standards of bibliographic description, and to enable the student to apply bibliographic standards to specific cases. | |||||||||