The curriculum is structured around a core foundational area that develops essential competencies in big data analysis grounded in an understanding of humanity, society, and information, complemented by three advanced specialization areas that students may customize according to their individual academic and professional goals.
This foundational component develops essential competencies by examining the evolution of civilization through the Fourth Industrial Revolution, with a focus on the characteristics, value, and effective utilization of information. Practical training emphasizes hands-on big data analysis using Python and R, with applications across social sciences, business, and natural sciences.
Advanced Specialized Tracks- Data Science Convergence
- As an advanced specialization in big data analysis, this track covers data analysis, utilization, and strategic planning, cultivating professionals equipped with expertise in big data programming, analysis, and applied solutions.
- AI Business Convergence
- Grounded in artificial intelligence technologies such as machine learning, deep learning, and generative AI, this track enables students to analyze emerging business models and develop competencies in AI-driven business applications and innovation.
- Human Science Convergence
- This track develops data-driven problem-solving and decision-making capabilities in areas such as social welfare, healthcare, environmental policy, and public governance, addressing real-world societal challenges through analytical methodologies.
Courses
| Course Title | |
|---|---|
| 1st semester | 2nd semester |
Core courses
| Basic Big Data Analytics | Statistical Analysis |
| Decision Making and Problem Solving | Machine Learning and Big Data Analysis |
| Advanced Technology Seminar : Smart Computing | Seminar on Interdisciplinary Information Studies |
Advanced Courses
| Integrated Data Sciences |
AI Basics | Advanced AI(Deep Learning) |
|---|---|---|
| Data Analysis Planning | Big Data Research Methods | |
| Big Data Analysis and Application : Text Data Analysis | AI Platform | |
| Practical Big Data Analytics | AI-based Recommender Systems | |
| Introduction to Reinforcement Learning and Applications | AI Ethics and Trust | |
| AI Quality and Software Engineering | ||
| Integrated AI Business |
Understanding and Applying Generative AI | Data Driven Prediction |
| AI Service Planning | Digital Marketing | |
| Integrated Human Sciences |
Health Technology Informatics Seminar | Health and Welfare Data Analysis |
| Sustainable Development and ESG Management | Art of the Digital Age | |
| Social Science Research Methods |
Seminar and
Thesis Research
| Project Semina (For Master’s Degree Program) |
| Master’s Thesis Research I |
| Master’s Thesis Research II |
| Doctoral Dissertation Research I |
| Doctoral Dissertation Research II |