Data Science Center

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PRI200LD(情報学基礎 / Principles of informatics 200)
The Basics of Applied Data Science A

Yasushi KODAMA, Miki TAKATA, Teruhiko UNOKI, Kunihiko TAKAMATSU, Makoto MIYAZAKI

Class code etc
Faculty/Graduate school Data Science Center
Attached documents
Year 2022
Class code A9993
Previous Class code
Previous Class title
Term 秋学期授業/Fall
Day/Period 集中・その他/intensive・other courses
Class Type
Campus
Classroom name 各学部・研究科等の時間割等で確認
Grade
Credit(s) 2
Notes
Open Courses
Open Courses (Notes)
Global Open Courses
Interdepartmental class taking system for Academic Achievers
Interdepartmental class taking system for Academic Achievers (Notes)
Class taught by instructors with practical experience

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Outline (in English)

[Course Outline(in English)]
You can learn mathematics, data science and AI in a complementary and developmental way. You can acquire the ability to extract meaning from data and provide feedback to the field, as well as the basic ability to utilize AI to solve problems, focusing on the operational aspect.
So you will acquire a broad perspective for your own fields to apply mathematics, data science, and AI.
[Learning Objectives]
Using the basic concepts, methods and application examples of data science and data engineering, you can understand methods for extracting meaning from data and providing feedback to the field.
[Learning Activities Outside of Classroom]
The standard preparatory study and review time for this class is 2 hour each. Work on quizzes, etc, that are imposed online.
[Grading Criteria/Policy]
Evaluation is based on the total score of each check test(70%),in-class comprehensive test(final test) and submission of each questionnaire(30%). Please note that each check test has a deadline.

Default language used in class

日本語 / Japanese