Overview

Curriculum

Master’s course

Master’s course

You need to earn at least 18 credits from Major subjects inyour department/course and at least 10 credits from AIQDS
subjects listed on the other page, where AIQDS subjects areregarded as Related subjects in your department/course. Intotal, at least 30 credits are obligatory for graduation.

Fall Semester
Fundamentals of Data Sciences

At least 30 credits in total
At least 10 credits
from AIQDS subjects

At least 18 credits fromMajor subjects in yourdepartment/course

AIQDS Subjects provided by GSIS
Fundamentals of Data Sciences

Take at least 2 subjects（1 subject = 2 credits）- Sensing- Storage- Computing

Subjects for Data Sciences

Take at least 2 subjects（1 subject = 2 credits）

Data Science Basic

Information Ethics

Interdisciplinary Information Sciences

Legal System in Information Society

Subjects for Data Sciences

DataSciencesⅠ

Spring Semester

Take at least 1 subject from each categoryⅠ,Ⅱ, Ⅲ（ 1 subject = 2 credits）

High-Performance Computing

Computer Structures

Computer Architecture

Theory of Differential Equations

Information and Communications Technology (Odd-numbered year only)
Foundations of Software Science (Odd-numbered year only)Internet and Information Security（Intensive course）

Take at least 1 subject from each categoryⅠ,Ⅱ,Ⅲ（1 subject = 2 credits）

Computer Vision

Physical Fluctuomatics

Training Subjects（1 subject = 1 credit）

Design and Analysis of Information Systems (Odd-numbered year only)Intelligent Systems Science (Odd-numbered year only)

Natural Language Processing

Intelligent Control Systems (Even-numbered year only)

Statistical ModelingGame Theory for Applied Economics

Cryptology

IT Fundamental（Intensive course）

Big Data Skill Up Training For those who are not so familiar with mathematicaland statistical calculations using R and Python, please take this subject
Data Science Training Camp Ⅰ,Ⅱ ※Compulsory subject【Option】Internship（1-2 credits）

Data
Sciences Ⅱ- Analysis- Mining

Doctor’s course

Spatial Information Analysis

Although the doctor's course students are expected todevote themselves mostly to their own research work,
Advanced SeminarsⅠ,Ⅱ and Big Data Challenge arecompulsory for them to complete the AIQDS program.

CS Fundamentals（Intensive course）

High Light

Learning Japanese Language & Culture
The participants are highly encouraged to learn
Japanese language and culture, because this is one ofprimary reasons for studying abroad.
"Tohoku University Japanese Language Program atKawauchi" offers you a wide variety of opportunities oflearning including an e-learning system.
http://www.he.tohoku.ac.jp/SJLE/JLPK/guide-e.pdf

DataSciences Ⅲ

Spatial Economics

Mathematical Urban Modeling

Applied Intelligence Software

System Control Science- Problem Solving- Design

Applied Data Sciences

Training Subjects（1 subject = 1 credit）
Big Data
Skill Up Training※Data Science
Training Camp

Training of R and Python

Training of R and Python

Training CampⅠ, Training CampⅡ

Training CampⅠ, Training CampⅡ※Compulsory for Master’s course students

Doctor’s course※Advanced SeminarⅠ,Ⅱ

Data science-related meetings, symposia, and conferences assigned by AIQDS（1 credit each）※Big Data Challenge

Project-based learning based on knowledge and skills of data science（2 credits）※Compulsory for Doctor’s course students