The Spring semester of the first year is always done at University of Tsukuba (UT), in Japan. The list of the courses is given below and is detailed after. Students should valid at least 8 Japanese credits (which will be recognized as 30 ECTS).
- Special Lecture on Numerical Simulation (2 Japanese credits)
- Experiment Design in Computer Sciences (2 Japanese credits)
- Topics in Computer Science I (1 Japanese credit)
- Data Engineering I (2 Japanese credits)
- Computational Science Literacy (1 Japanese credit)
- Advanced Project in Practical AI (1 Japanese credits)
- Advanced Project in Practical Data Science I (1 Japanese credit)
- Advanced Project in Practical Data Science II (1 Japanese credit)
Special Lecture on Numerical Simulation (2 Japanese credits)
Lecturer: Dongsheng Cai
Abstract: In this course we learn how to solve simulation problems in engineering, chemistry, medical science, and economy using computer algorithms. Specifically, we deal with physical models using finite difference method, relaxation method, entropy maximization, fractal, and artificial, and chaos theory and its application.
Experiment Design in Computer Sciences (2 Japanese credits)
Lecturer: Tetsuya Sakurai, Aranha Claus
Abstract: In this course we will study how to design and perform scientific experiments in the context of Computer Science research, with the goal of producing sound Scientific results. Topics include techniques for parameter and experiment selection, and statistical methods for analysis of results.
Topics in Computer Science I (1 Japanese credit)
Lecturer: Aranha Claus etc
Abstract: In this course researchers covering diverse research areas in computer science give talks on recent advances in their research domain.
Data Engineering I (2 Japanese credits)
Lecturer: Hiroyuki Kitagawa, Toshiyuki Amagasa, Hiroaki Shiokawa
Abstract: In this course students learn techniques in data engineering and data mining to deal with big data. Specifically, we first review basics of databases, and then cover association rule mining, basic classifiers, such as decision tree and naive Bayes classifier, clustering and graph processing.
Computational Science Literacy (1 Japanese credit)
Lecturer: Hiroyuki Kusaka, etc.
Abstract: Computational Science is a forefront approach in science and technology solving complex problems with supercomputers. It is recognized as an indispensable approach equal to experiments and theory in many research fields. It is highly recommended for those who will be working in research of any fields to learn basic knowledge and methodology of computational sciences. In this lecture, professors belonging to Center for Computational Sciences will overview researches with computational method in various fields of science. The lecture aims to provide a literacy of computational method and a comprehensive view across scientific fields through computational approaches.
Advanced Project in Practical AI (1 Japanese credits)
Lecturer: (TBD)
Abstract: In this course students will engage in a project work in different area of research related to AI: Practical AI system with machine learning and deep learning, AI and robotics, IoT and sensor network, human agent, social robotics
Advanced Project in Practical Data Science I (1 Japanese credit)
Lecturer: (TBD)
Abstract: In this course students will engage in a project work in different area of research related to data science: Heal promotion and policy, sport and biomechanics, cognitive engineering, health service research, Medical science, humanics, bioinformatics
Advanced Project in Practical Data Science II (1 Japanese credit)
Lecturer: (TBD)
Abstract: In this course students will engage in a project work in different area of research related to data science: HCI, VR, computer music and audio interface, library informatics, next-generation mobility