With the advancement of information and communication technologies, a vast amount of data is being collected, and data-driven analysis and decision-making are increasingly emphasized across various media and platforms. This course aims to provide fundamental knowledge of statistical analysis by covering basic concepts as well as inferential statistical methods such as t-tests, ANOVA, and regression analysis, thereby enabling students to understand data and acquire foundational skills for media big data analysis. 

This course covers fundamental analytical methods and programming skills for collecting, analyzing, and utilizing data in media research and practice. Students will learn the basic use of R, a statistical programming language, and apply various analytical techniques through hands-on practice using media data.  

Text mining refers to the process of extracting meaningful concepts or features from text and deriving high-quality information. As an introductory course to the analysis of unstructured data (text), this course teaches methods for analyzing text data collected from social media and websites using programming languages.  

This course aims to provide an understanding of the concepts, history, and key algorithms of recommender systems used in media platforms to deliver personalized content. It also examines how these systems are applied in real-world service environments. By comprehensively learning the design principles, implementation methods, and performance evaluation techniques of content recommendation algorithms, students will develop practical problem-solving skills.

This course examines the transformative changes in innovative information and communication technologies and explores how governments intervene through laws and policies in this field. It analyzes how rapidly evolving ICT and public policy interact in a complementary manner within the digital media industry, shaping its ongoing development and transformation.

This course covers theories related to the industrial structure and ecosystem of the broadcasting and OTT sectors, and analyzes key industry trends, their background and implications, as well as the perspectives of various stakeholders. Through this, students will develop the ability to interpret the diverse services offered to users in the broadcasting and OTT markets from an industry and ecosystem perspective and to analyze competitive and survival strategies.  

This course aims to help students understand the principles and applications of generative AI and develop the ability to design effective prompts that produce desired outcomes. It covers everything from the basics of using ChatGPT to advanced prompt design, as well as document structuring with Markdown, content creation, and brainstorming techniques. Students also learn practical skills such as data analysis, web data collection, workflow automation, and image generation. In addition, the course includes building customized chatbots using GPTs, equipping students with practical competencies to apply AI across various fields.