学部・大学院区分 Undergraduate / Graduate		農・博前

時間割コード Registration Code		2930011

科目区分 Course Category		Ｃ類 Category C

科目名　【日本語】 Course Title		データサイエンス特別講義５

科目名　【英語】 Course Title		Special Lecture on Data Science 5

コースナンバリングコード Course Numbering Code

担当教員　【日本語】 Instructor		西内　俊策 ○

担当教員　【英語】 Instructor		NISHIUCHI Shunsaku ○

単位数 Credits		1

開講期・開講時間帯 Term / Day / Period		秋集中その他その他 Intensive(Fall) Other Other

対象学年 Year		１年 1

授業形態 Course style

授業の目的　【日本語】
Goals of the Course(JPN)

授業の目的　【英語】
Goals of the Course

The aim of this class is to help students acquire programming skills that will be useful for important analytical work in research.
Specifically, students will learn to program the process of pre-processing and visualization of data obtained in research activities, which is necessary to ensure the reproducibility of the analysis work.

到達目標　【日本語】
Objectives of the Course(JPN)

到達目標【英語】
Objectives of the Course

By the end of the course, students should be able to do the following:
1. Apply data preprocessing to aid in the analysis and visualization.
2. Use Markdown in R and/or Python to aid in the basic visualization of experimental data.

授業の内容や構成
Course Content / Plan

Contents:
1. Introduction: What is a tidy data? The importance of data preprocessing.
2. Introduction: What is your data? How do you visualize your data?
3. Preparing for data preprocessing and visualization: Select and install library.
4. Preparing for data preprocessing and visualization: Plan for data preprocessing and visualization.
5. Data preprocessing.
6. Data visualization.

Students should bring their own PC with Anaconda or Rstudio. Student may bring their own experimental data for analysis and visualization.

履修条件・関連する科目
Course Prerequisites and Related Courses

Students should acquire the credits for “Data Sciences 1”, “Data Sciences 2”, and “Data Sciences 3” before this course.

成績評価の方法と基準
Course Evaluation Method and Criteria

Grading will be decided based on attendance and the quality of the students’ programming performance.

教科書・テキスト
Textbook

Will be introduced in the class.

参考書
Reference Book

Will be introduced in the class.

課外学習等（授業時間外学習の指示）
Study Load(Self-directed Learning Outside Course Hours)

Preparation and Review

使用言語
Language Used in the Course

授業開講形態等
Lecture format, etc.

Remote class (Zoom)
If there are any changes to the class format after registration, the information will be posted on the NUCT class website.

遠隔授業（オンデマンド型）で行う場合の追加措置
Additional measures for remote class (on-demand class)

You can use the NUCT "Message" to ask questions to the lecturer.