Graduate School of Data Science: Department of Health Data Science
Throughout history, up until the present, health issues have always been one of the biggest concerns of humankind. However, with the advancement in technology, countless of new ways are being created to tackle the various health issues around the world – and one of these problem-solving methods involve the usage of data. Advanced data science personnel can now integrate their knowledge in data science with the expertise of those in the medical field.
As the only university in Japan that combines the Faculty of Medicine and the Department of Data Science, our Graduate School of Data Science's Department of Health Data Science provides practical learning and leads the development of data science human resources.
As the only university in Japan that combines the Faculty of Medicine and the Department of Data Science, our Graduate School of Data Science's Department of Health Data Science provides practical learning and leads the development of data science human resources.
OVERVIEW
- Degree awarded Master of Health Data Science
- Duration 2 Years (MDS)
- Medium of instruction Japanese
- Study in English Not available
- Language requirements JLPT N2 or higher, IELTS/TOEFL-ITP/TOEIC IP
- Non-degree program Not available
STRUCTURE
Course Structure
Master's program
For the purpose to illustrating the curriculum of this programme, most of the following course names have been roughly translated from Japanese.
| M1 Sem 1 | M1 Sem 2 | M2 Sem | |
|---|---|---|---|
| Biostatistics I (2) | Biostatistics II (2) | Clinical Prediction Rule（2） | Bioinformatics (1) |
| Research Design Studies (2) | Clinical Metrology (2) | Artificial Intelligence (1) | － |
| Research Ethics（1） | Big Data Analysis (1) | Health Technology Assessment (2) | － |
| Health Service Research (2) | Database Development Exercise (2) | Clinical Trial Methodology (1) | － |
| Literature Evaluation Method (1) | Evidence Lightweight Evaluation (2) | － | － |
| － | Health Data Science Research Exercise (4) Active learning in which specific research topics are proposed, concept design, implementation, and results are interpreted and presented, and faculty and graduate students conduct critical examinations of each other. |
－ | |
| Special Research Subjects (4) | Special Research Subjects (4) and Master's Thesis (0) | ||
Completion requirements: 30 credits
- Special Research and Exercises: 12 credits (4 units for Health Data Science Research (required) and 8 credits for seminars and thesis (required))
- Common subjects: 18 credits (lectures/exercises (required) 7 credits, lectures/exercises (choice) 11 credits or more)
Department of Health Data Science Faculty List
Click on the links below to view our Faculty List.