Lecture and Seminar Information
The Data Science Program is designed to allow students to take many cross-disciplinary courses that span the areas of data science, bioinformatics, and materials informatics. For details, please check the course classifications in the syllabus.
Note that the following courses are required
Fundermentals of Data Science (3039) 4/19 – 4/28
Data Science (4105) 6/3 – 8/19
Data Science PBL 1 (5013) Late Jul. (TBD) –
Data Science PBL 2 (5014) Late Oct. (TBD) –
The course requirements for the Data Science program for the 2022 academic year are listed below.
Please note that course requirements depend on your program.
In the Data Science Program, students must take,
- (i) One course from “Introduction to Information Science and Engineering,” “Introduction to Bioscience,” or “Introduction to Materials Science and Engineering,” in the same area as your laboratory;
- (ii) One course in either “Biology with data science” or “Materials Informatics”
- (iii) Two courses from “Sequential Data Modeling,” “Visual Media Processing I,” “Data Mining,” “Multidimensional Signal Processing,” “Natural Language Processing,” “Mathematical Models in Biology,” “Advanced Techniques in Bioscience,” “Statistics and Mathematics in Bioscience,” “Light and Information Devices Special”.
About other individually scheduled practical training, lectures, and off-campus courses, please see below for detailed information,
Data Science Project Based Learning I,II
Special Lectures in Data Science
Kansai Consortium for Data-related Human Resource Development (in Japanese)