授業の目的 【英語】
Goals of the Course [ENG] | | | 【Standardized across all programs】 The goal of this course is for students to acquire basic skills in data analysis using programming and computer tools based on the knowledge acquired in the lectures in order to acquire data analysis skills that will become the foundation for creating new values in various situations in the society. Students will execute the calculations and analysis methods learned in the lecture by themselves using Python (Mostly for students in the sciences). |
|
|
授業の達成目標 【英語】
Objectives of the Course [ENG] | | | Students will learn basic skills for machine learning and programming through Python, based on the knowledge learned in the Introduction to Data Science course. |
|
|
授業の内容や構成
Course Content or Plan | | 1. Programming with Python (variables, arithmetic operations), Usage of Google Colaboratory
2. Programming with Python
3. Programming with Python (conditional structures, data structure)
4. Programming with Python (Functions)
5. Numerical calculation and visualization with Python (numpy, matplotlib)
6. Data processing and regression analysis with Python (pandas, scikit-learn)
7. Machine Learning with Python (scikit-learn)
8. Image Recognition with Python (scikit-image, dlib) |
|
|
履修条件・関連する科目
Course Prerequisites and Related Courses | | | No prerequisites are required. |
|
|
成績評価の方法と基準
Course Evaluation Method and Criteria | | Based on assignments and quizzes. The assignments will count for 80%, and quizzes count for 20%.
A total of at least 60% is needed for passing this course.
No notice is necessary for withdrawing from the course. If the number of the assignment submitted is 3 or less the grade will be "W". |
|
|
教科書
Textbook | | | There is no specific textbook, but materials will be provided for each class. |
|
|
参考書
Reference Book | | | 喜多一，プログラミング演習2019（http://hdl.handle.net/2433/245698） |
|
|
課外学修等
Study Load (Self-directed Learning Outside Course Hours) | | | Students are encouraged to learn Python outside of the class in order to be able to solve the assignment and quizzes. |
|
|
注意事項
Notice for Students | | Since we will use Google Colaboratory in this course to code in Python, it is desirable to prepare a computer that can use a web browser (Firefox, Chrome, or Safari is recommended). A Google account is required to use Google Colaboratory, so be sure to obtain one in advance.
Please check the course homepage for regular updates: https://www.henrikbachmann.com/DataScienceB2025.html |
|
|
本授業に関するWebページ
Reference website for this Course | | |
|
担当教員からのメッセージ
Message from the Instructor | | |
|
実務経験のある教員等による授業科目（大学等における修学の支援に関する法律施行規則に基づくもの）
Courses taught by Instructors with practical experience | | |
|
授業開講形態等
Lecture format, etc | | C-3）Remote course（Mainly remote classes using both simultaneous interactive and on-demand method. Some of the classes are face-to-face）
* Classrooms for face-to-face classes can be found in Timetable B on the ILAS website. |
|
|