Master's Program
Data Science Foundation
Students must take at least 3 courses from Data Science Foundation courses (take at least 1 course from each category Data Science I, Data Science II, and Data Science III). And it must include at least 1 course from the courses marked with * (star).
* Syllabus can be found on the following page
Data Science I
~Technology Innovation~
These courses are designed to develop students’ ability to invent new technologies by combining new sensing techniques and existing data and/or build systems of sensing, storage, communication, or computation.
- [Spring] Computer Structures
- [Spring] Intelligent Integrated Systems
- [Spring] Highly-Reliable System Design
- [Fall] High-Performance Computing
- [Fall] Computer Architecture
- [Fall] Foundations of Software Science
- [Fall Intensive] Internet and Information Security
Data Science II
~Data Analytics~
These courses are designed to develop students’ ability to extract necessary information from big data and plan to organize and perform big data analysis.
- [Spring] Machine Learning Basics*
- [Spring] Physical Fluctuomatics
- [Spring] Intelligent Systems Science (Odd-numbered year only)
- [Spring] Intelligent Control Systems (Even-numbered year only)
- [Fall] Natural Language Processing
- [Fall] Statistical Modeling
- [Fall] Cryptology
- [Fall] Computer Vision
- [Fall] Advanced Applied Data Analysis
- [Fall] Mathematical Informatics
- [Fall] Fundamental Artificial Intelligence
- [Fall] Design and Analysis of Information Sciences (Odd-numbered year only)
- [Spring Intensive] Information Technology Fundamental
- [Fall Intensive] Computer Science Fundamentals
- [Spring] Econometrics I
- [Fall] Econometrics II
Data Science III
~Problem Finding and Solving~
These courses are designed to develop students’ ability to find fundamental problems and formulate processes to solve them.
- [Spring] Information Ethics*
- [Spring] Legal System in Information Society*
- [Spring] Mathematical Urban Modeling
- [Spring] System Control Engineering I
- [Fall] Interdisciplinary Information Sciences*
- [Fall] Applied Data Sciences
- [Fall] Information Biology
- [Fall] Applied Intelligence Software
- [Fall] Spatial Economics
- [Fall] Data Science for Urban Transportation System
- [Fall] Information Content
- [Fall Intensive] Advanced Integrative Life Sciences I (Brain and Nervous System)
- [Fall Intensive] Advanced Ecological Developmental Adaptability Life Sciences II (Ecological Dynamics)
- [Spring/Fall Intensive (Spring English/Fall Japanese)] Advanced Molecular and Chemical Life Sciences II (Molecular and Network Genomics)
Practical training
- [Spring Intensive] Data Science Programming Basics (1 credit・Optional)
- [Spring Intensive] Data Engineering (1 credit・Compulsory)
- [Spring Intensive] Data Science Training I (1 credit・Optional)
- [Spring Intensive] Data Science Training II (1 credit・Compulsory)
Short-term Overseas Training
- Short-term Overseas Training (1 credit・Optional)
In this optional training, Master’s students are supported to stay at an institution abroad to participate in a short-term overseas training (8-14 days). Please contact the office of your department about financial support for traveling expenses.
Master’s thesis and the seminar
- Master’s thesis and the seminar (10-16 credits・Compulsory)
Please contact your the office of your department about the content of the seminar.
Doctoral program
Project training
- Data Science Challenge (2 credits・Compulsory)
This course is designed to provide opportunities to use learned skills to deal with and analyze big data and lead a group to solve practical problems.
Overseas Training
- Data Science Special Training (3 credits・Compulsory)
Doctoral students must stay at an institution abroad for at least 6 months and conduct a collaborative research.
Advanced Seminars
- Advanced Seminar I (1 credit・Compulsory)
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Advanced Seminar II (1 credit・Compulsory)
Details will be announced by the GP-DS office.
Doctor’s thesis and the seminar
- Doctor’s thesis and the seminar (10-16 credits・Compulsory)
Please contact the office of your department about the content of the seminar.
Note: Six credits of Data Sciences I, II, III are compulsory also for the students who participate in the GP-DS program after entering Doctor's course.