社会学研究科の授業情報

サイトトップへ戻る

サイトトップ > 社会学研究科授業情報 > 社会学研究科講義科目

社会学研究科講義科目

※ 当該講義情報の詳細は 本学学務情報システム・学生ポータル CELS を参照してください。

研究科共通科目 先端社会科学 4709 A 冬 集中  2単位

Data Processing for Social Sciences (Intermediate)

担当教員:ジョナサン・ルイス
【教授言語】

英語

【学部・学年の指定】

無し

【授業科目の目的と概要】

If you want to collect and use data (whether numbers, text or both) for your research project, you need to know the basics of programming as well as how to collect, clean, store and filter data. This course aims to get you up that learning curve as quickly as possible, using the excellent interactive online lessons provided by Datacamp.

I will be available in the classroom to answer any questions you have, but please be aware that this course is about following the online course and not about me explaining everything. If you cannot understand the Datacamp lessons then I will not be able to help you cover all the units in time and you will not pass the course.

【授業の内容・計画】

The Ministry of Education expects that students will spend an equal amount of time studying out of class (preparing and revising) as they do in class. We have 13 classes of 105 minutes each, therefore students should study a total of 13 x 105 x 2 minutes, which is 45 hours and 30 minutes.

The "Data Scientist with Python" Career Track on DataCamp offers 22 units (courses) totalling 84 hours.
https://www.datacamp.com/tracks/data-scientist-with-python

Students are therefore required to complete at least the first 12 units, totalling 44 hours. Namely:

1. Introduction to Python
https://www.datacamp.com/courses/intro-to-python-for-data-science
4 hours

2. Intermediate Python for Data Science
https://www.datacamp.com/courses/intermediate-python-for-data-science
4 hours

3. Python Data Science Toolbox (Part 1)
https://www.datacamp.com/courses/python-data-science-toolbox-part-1
3 hours

4. Python Data Science Toolbox (Part 2)
https://www.datacamp.com/courses/python-data-science-toolbox-part-2
4 hours

5. Importing Data in Python (Part 1)
https://www.datacamp.com/courses/importing-data-in-python-part-1
3 hours

6. Importing Data in Python (Part 2)
https://www.datacamp.com/courses/importing-data-in-python-part-2
2 hours

7. Cleaning Data in Python
https://www.datacamp.com/courses/cleaning-data-in-python
4 hours

8. pandas Foundations
https://www.datacamp.com/courses/pandas-foundations
4 hours

9. Manipulating DataFrames with pandas
https://www.datacamp.com/courses/manipulating-dataframes-with-pandas
4 hours

10. Merging DataFrames with pandas
https://www.datacamp.com/courses/merging-dataframes-with-pandas
4 hours

11. Intro to SQL for Data Science
https://www.datacamp.com/courses/intro-to-sql-for-data-science
4 hours

12. Introduction to Databases in Python
https://www.datacamp.com/courses/introduction-to-relational-databases-in-python
4 hours

【テキスト・文献】

https://www.datacamp.com/tracks/data-scientist-with-python

このページの一番上へ