This is a 7-session online course designed for students (from junior high to graduate level) who want to learn data science from the beginning. The curriculum covers fundamental Python programming (4 sessions) and an introduction to data science with practical exercises (3 sessions). You will learn Python syntax, data visualization, and how to build predictive models using multiple regression analysis. The course content is supervised and developed by the Matsuo-Iwasawa Laboratory at the University of Tokyo, drawing on over a decade of experience in AI talent development. Lectures are delivered live, followed by hands-on exercises. A basic understanding of high school level mathematics is sufficient.
The course consists of 7 live online sessions via Zoom, scheduled primarily on Thursdays from 19:00 to 20:30 JST. One session is scheduled for Wednesday, August 12th. Some sessions may have extended times. Archived videos will be available for later viewing. A final coding assignment will be given.
Applicants must have a high school level of mathematics. A commitment to attend lectures and submit assignments is required, along with an estimated 2 hours per week for assignments.
While this course is free for students, some other programs offered by the university may have fees.
Applicants must be currently enrolled in or accepted to a school (junior high to graduate level) and have a basic understanding of high school level mathematics. Proof of student status is required.
This course is free of charge for all students.
The course consists of 7 live online sessions, primarily held on Thursdays from 19:00 to 20:30 JST, with one session on Wednesday, August 12th. Archived videos are also available.
The lectures are delivered live via Zoom. The language of instruction is not specified in the provided data.
The deadline for ID registration on the Omnicampus platform is July 21, 2026, 10:00 AM JST, and the course application deadline is July 23, 2026, 10:00 AM JST.
Acquiring skills in data science and Python can be a significant asset for your future career, providing a strong foundation for more specialized learning and practical application in handling data.