Graduate education
Data Science Master Program
Competence Points
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DSMP (Data Science Master Program)
Registration Key: 1703750
[DSMP Completion Requirements]
| Competence | RequiredPoints | |
|---|---|---|
| MDA Fundamental Skills | Fundamental knowledge and practical abilities in data science and AI required to become a Data Science Expert | 2 or more |
| MDA Interdisciplinary Skills | Ability to apply data science and AI knowledge and skills through exposure to advanced research and real-world challenges faced by leading domestic and international research institutions and companies | 2 or more |
| MDA Specialized Skills | Specialized knowledge and practical abilities related to data science and AI within the student's major field of each degree program | 6 or more |
Courses Related to DSMP
MDA Fundamental Skills + MDA Interdisciplinary Skills
| Course | Overview |
|---|---|
| Advanced Course in Data Science | This course provides a systematic introduction to fundamental and advanced methods for analyzing, interpreting, and predicting diverse types of data, with an emphasis on understanding the principles and characteristics of each technique. Through lectures and hands-on exercises using Python, students will develop practical skills for objective, data-driven evaluation and problem solving. |
MDA Interdisciplinary Skills
| Course | Overview |
|---|---|
| MDA InterdisciplinaryCollaborativeSeminar | Omnibus classes will be conducted by experts in the fields of mathematics, data science, and AI (MDA) from researchers, companies, and local governments in Japan and abroad, as well as featuring lectures on recent significant issues. The primary objective of these classes is to nurture problem-solving skills and foster innovation by leveraging MDA methodologies and integrating knowledge from other interdisciplinary fields. |
| MDA Special Exercise for Top-level Human Resource Training | Students participate in project-based learning (PBL) courses based on real-world challenges and datasets provided by companies, local governments, and other organizations. |
| Advanced Project Research | Develop research capabilities to utilize data for problem-solving through collaborative research or internships focused on addressing real-world challenges faced by companies, government agencies, and research institutions (hereinafter referred to as "organizations"), as well as on leveraging the data they possess. |
| MetaverseEngineeringWorkshop | Students learn methods for developing avatars and 3D environment models to create immersive communication environments in the metaverse, as well as user experience (UX) design and evaluation methods, seamless integration between real-world and metaverse environments, the integration of generative AI, and the associated ethical considerations. They also gain practical experience in designing and implementing metaverse-based environments that facilitate communication among students, external researchers, and industry participants, thereby promoting discoveries and the creation of new knowledge that contribute to research and career development. |
| Metaverse Engineering Workshop | This course is intended for first- and second-year master's students and aims to provide an understanding of how research and development is conducted in companies, government agencies, and research institutions (hereinafter referred to as "organizations") to address real-world challenges. Through case studies presented by researchers holding doctoral degrees and working in organizations active in the fields of Mathematics, Data Science, and Artificial Intelligence (MDA), students gain insight into cutting-edge research practices. In addition, by receiving expert and practical feedback on their own research from doctoral researchers in these organizations, students develop the ability to: (1) relate their research to real-world challenges; (2) engage in constructive discussions with experts from diverse disciplines and industries; and (3) communicate their research outcomes clearly and effectively. |
MDA Practical Research Exercises
List of Courses Eligible for Competency Acquisition
(as of April 2026)
MDA Fundamental Skills
| CS | Advanced Course in Data Science |
| IMIS | Machine Learning Natural Language Processing and Information Access Artificial Intelligence Fundamental Theory of Intelligent Interaction Systems Tools and Practices for Intelligent Interaction Systems A |
| Informatics | Machine Learning and Pattern Recognition |
MDA Interdisciplinary Skills
| CS | Advanced Course in Data Science |
| SIE | MDA Interdisciplinary Collaborative Seminar MDA Special Exercise for Top-level Human Resource Training Advanced Project Research Metaverse Engineering Workshop MDA Practical Research Exercises |
| IMIS | Seminar in Intelligent and Mechanical Interaction Systems I |
MDA Specialized Skills
| PPS | Social Simulation Game Theory Statistical Analysis Corporate Valuation Spatial Information Science Urban and Regional Analysis Theory and Practice of Economic Policy Information Security Theory of Asset Valuation Discrete Mathematics Mathematical Optimization Theory Microeconometric Analysis Operations Management Special Lecture on Policy and Planning Sciences I Special Lecture on Policy and Planning Sciences II Special Lecture on Policy and Planning Sciences III |
| SE | Analysis of Service Satisfaction Special Lecture on Service Engineering I Special Lecture on Service Engineering III Consumer Psychology Regional Data Analysis Big Data Analytics Applied Optimization Management of Technology |
| R2E | Introduction to Soft Computing Data Mining Advanced Course on Cryptography Advanced Information Systems Advanced Course on Mathematical Model Analysis Theoretical Environmental Analysis Seminar in Modeling of Energy and Environment Systems Advanced Course in Cyber Risk Philosophical Scientific Perspectives on Risk and Safety Advanced Course in Network Security Seminar in Human Factors Human Factors Seminar in Resilient Urban Planning Financial Risk Analysis Advanced Course on Cyber Security Cognitive Interface Design Financial Cryptography and InformationSecurity Web Application Security Intelligent Systems Systems Design Theory Advanced Lectures of Information Retrieval Intellectual Document Control Complex Systems |
| CS | Advanced Course in Computer Graphics Systems and Optimization Systems and Control Data Engineering I Data Engineering II Special Topics in Computer Human Interaction I Special Topics in Computer Human Interaction II Advanced Course in Programming Languages Image Recognition and Understanding Basic Computational Biology Advanced Course in Computational Linguistics Advanced Course in High Performance Computing Advanced Course in Signal and Image Processing I Advanced Course in Signal and Image Processing II Advanced Course in Signal and Image Processing III Advanced Course in Computational Algorithms Adaptive Media Processing Concurrent Systems Advanced Parallel Processing Architecture Special Lecture on Cryptography I Special Lecture on Cryptography II Topics in Computer Ethics Topics in Computer Science I AI Social Practice A AI Social Practice B Special Topics in Quantum Information Science |
| IMIS | Cybernics System Modeling Smart Info-media System Fundamentals of Electrical Communication Usability Testing Real-World Oriented Sensing Information and Coding Theory Bioinstrumentation Engineering Extended Perception Engineering Fundamentals of Mathematics in Intelligent and Mechanical Interaction Systems Fundamental Mathematical System of Mechanical Interaction Systems Statistical Data Analysis for Intelligent and Mechanical Interaction Systems Tools and Practices for Intelligent Interaction Systems B |
| EME | Advanced Structural Mechanics Advanced Fluid Mechanics Advanced Computational Mechanics Computational Fluid Dynamics Advanced Reliability Engineering |
| EMP | Methods of Experimental Psychology Exercises of Machine Learning |
| LSI | Introduction to Bioinformatics Biomolecule and Medical Informatics Gene Analysis and Functional Genomics Machine Learning in Practice |
| Infomatics | Practical Data Science Visualization Biological and Life Informatics Structured Data Music and Information Information Access Practical Data Science Visualization Biological and Life Informatics Structured Data Music and Information Information Practices Recommendation Systems Human Computer Interaction Digital Humanities Human Computer Interaction Digital Humanities Information Practices Recommendation Systems Human Computer Interaction Digital Humanities Information Organization Information Organization Information Organization Survey and Data Analysis Survey and Data Analysis Survey and Data Analysis Behavioral Economics Behavioral Economics |