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データサイエンス応用演習
| 令和２年度入学者 | データサイエンス応用演習 | ||||
|---|---|---|---|---|---|
| 令和元年度以前入学者 | 社会学実証応用演習３ | ||||
| 教員名 | 菅野剛 | ||||
| 単位数 | 1 | 課程 | 開講区分 | 文理学部 | |
| 科目群 | 社会学専攻 | ||||
| 学期 | 後期 | 履修区分 | 選択 | ||
| 授業の形態 | On demand (NU-AppsG and Google Classroom) |
|---|---|
| 授業概要 | Programming and Data Science |
| 授業のねらい・到達目標 | Learn programming. Learn statistics. Reduce cognitive biases. |
| 授業の方法 | https://sites.google.com/a/nihon-u.ac.jp/sugano-lab/home/google-classroom Classes to be held online. If the first class is not held in the classroom, please refer to the above web page and join the Google Classroom class. In some cases, online instruction is available with Google Classroom, etc. Preparation for class by reading textbooks and by learning online resources beforehand is required. Discuss about the topics and applied data analysis during the class. Programming and analyses are provided as pre-course work and homework. NU-MailG accounts and joining to Google Classroom are required. (BYOD: Bring your own device. ASUS Chromebook Flip C100PA / C101PA available for students.) We do not provide support for the Windows operating system due to shortage of human resource. Courses are to be closed upon no registration. |
| 授業計画 | |
|---|---|
| 1 |
Classroom: Notification of NU-AppsG accounts, password reminder settings, password settings, how to use Google Classroom, joining a class, Google Colaboratory, Python, Introduction to Programming and Data Science.
【事前学習】Pre-course work: Introduction to Programming and Data Science （2時間） 【事後学習】Homework: Introduction to Programming and Data Science （2時間） |
| 2 |
Optimization and the Knapsack Problem
【事前学習】Pre-course work: Optimization and the Knapsack Problem （2時間） 【事後学習】Homework: Optimization and the Knapsack Problem （2時間） |
| 3 |
Decision Trees and Dynamic Programming
【事前学習】Pre-course work: Decision Trees and Dynamic Programming （2時間） 【事後学習】Homework: Decision Trees and Dynamic Programming （2時間） |
| 4 |
Graph Problems
【事前学習】Pre-course work: Graph Problems （2時間） 【事後学習】Homework: Graph Problems （2時間） |
| 5 |
Plotting
【事前学習】Pre-course work: Plotting （2時間） 【事後学習】Homework: Plotting （2時間） |
| 6 |
Stochastic Thinking
【事前学習】Pre-course work: Stochastic Thinking （2時間） 【事後学習】Homework: Stochastic Thinking （2時間） |
| 7 |
Random Walks
【事前学習】Pre-course work: Random Walks （2時間） 【事後学習】Homework: Random Walks （2時間） |
| 8 |
Inferential Statistics
【事前学習】Pre-course work: Inferential Statistics （2時間） 【事後学習】Homework: Inferential Statistics （2時間） |
| 9 |
Monte Carlo Simulations
【事前学習】Pre-course work: Monte Carlo Simulations （2時間） 【事後学習】Homework: Monte Carlo Simulations （2時間） |
| 10 |
Sampling and Standard Error
【事前学習】Pre-course work: Sampling and Standard Error （2時間） 【事後学習】Sampling and Standard Error （2時間） |
| 11 |
Experimental Data Part 1
【事前学習】Pre-course work: Experimental Data Part 1 （2時間） 【事後学習】Homework: Experimental Data Part 1 （2時間） |
| 12 |
Experimental Data Part 2
【事前学習】Pre-course work: Experimental Data Part 2 （2時間） 【事後学習】Homework: Experimental Data Part 2 （2時間） |
| 13 |
Machine Learning
【事前学習】Pre-course work: Machine Learning （2時間） 【事後学習】Homework: Machine Learning （2時間） |
| 14 |
Statistical Fallacies
【事前学習】Pre-course work: Statistical Fallacies （2時間） 【事後学習】Homework: Statistical Fallacies （2時間） |
| 15 |
Programming and Data Science
【事前学習】Pre-course work: Programming and Data Science （2時間） 【事後学習】Homework: Programming and Data Science （2時間） |
| その他 | |
|---|---|
| 教科書 | 使用しない |
| 参考書 | John V. Guttag, Introduction to Computation and Programming Using Python: With Application to Understanding Data., The MIT Press, 2016, 2 edition P.G.ホーエル 『初等統計学』 培風館 1981年 第4版 T.H.ウォナコット・R.J.ウォナコット 『統計学序説』 培風館 1978年 長野宏宣・中川晋一・蒲池孝一・櫻田武嗣・坂口正芳・八尾武憲・衣笠愛子・穴山朝子 『IT技術者の長寿と健康のために』 近代科学社 2016年 Eric Grimson, John Guttag, and Ana Bell. 6.0002 Introduction to Computational Thinking and Data Science. Fall 2016. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/index.htm |
| 成績評価の方法及び基準 | 授業参画度(100%) Self-directedness and Intellectual flexibility. |
| オフィスアワー | Ask any questions at any time on Google Classroom. Appointment times will generally be available after the class. |
| 備考 | The content of the syllabus is subject to change based on the student's progress. Pre-class work and homework time is approximate. |