Course Introduction
Fundamental Data Science Course
Diversification and complication of information are creating problems that cannot be solved by any single existing academic field. In response to that, this course at the forefront of data science studies formulates a new methodology of data science dealing with culture, beyond the frameworks of mathematics, information and statistics and based on the knowledge accumulated in the respective fields.
Courses Offered
Master's Program
- Advanced Lectures in Numerical Analysis
- Advanced Lectures in Mathematical Modeling
- Advanced Lectures in Mathematical Statistics
- Advanced Lectures in Multivariate Analysis
- Advanced Lectures in Mathematical Foundation
- Advanced Lectures in Mathematical Sciences
- Advanced Lectures in Information Access Technologies
- Advanced Lectures in Database Systems
- Advanced Lectures in Biostatistics
- Advanced Lectures in Principles of Statistical Consulting
- Advanced Lectures in Time Series Analysis
- Advanced Lectures in Digital Signal Processing
- Advanced Lectures in Algorithms
- Advanced Lectures in Mathematical Optimization
Doctoral Program
- Extensive Lectures in Mathematical Modeling 1
- Extensive Lectures in Mathematical Modeling 2
- Extensive Lectures in Relational Data Analysis
- Extensive Lectures in Large Data Analysis
- Extensive Lectures in Mathematical Foundation
- Extensive Lectures in Mathematical Sciences
Thesis Title Examples
Master's Program
- Possibility of Penetration of Rabies into Hokkaido‐A Study with a Mathematical Model
- Research on the Decision of Information Unit for Understanding Document Content
- Understanding and Comparing Characteristics of Soccer Teams Using Sequentially Recorded Data
- Research on the Similarity Calculation Method for Complex Data
Doctoral Program
- Basic Research on Culture and Information Science and Ideal Types Modeling Analysis‐Concepts and Methods in Culture and Information Science‐
Faculty Members
HATANO Kenji
Professor
Research Field
data engineering, Internet information science, library and information science
Research Topic
Development of technology for effective storage, search and use of big data
Today’s advanced information society is not only seeing overflow of data but also its complexity. People solve various problems by collecting information from such data and acquiring new knowledge through using them. I teach students the skill to store, search and use appropriate data for solving the problems they deal with.
YADOHISA Hiroshi
Professor
Research Field
statistical science
Research Topic
Theoretical characterization of multivariate data analysis methods and development of a new method
My research interests include multivariate data analysis methods, social network analysis, sports data analysis, matrix decomposition-type multivariate analysis methods and symbolic data analysis methods. I teach students the theory and application of various methods of multivariate data analyses and provide them with the practical problem-solving skill using statistical science.