

【Python in English】Pandas Advanced (#202.2)
現地開催
参加枠
0人/定員8人
Free (無料)【先着順】無料
5人定員8人
| 参加枠 | 申込形式 | 参加費 | 参加者 |
|---|---|---|---|
Free (無料) | 先着順 | 無料 | 5人 / 定員8人 |
基本情報
- 日時
- 〜
- 開催形式
- 現地開催
- 会場
- 8 minutes from Ikebukuro Station (池袋駅から8分)
イベント内容
【Python in English】Pandas Advanced (#202.2)
About this course
This course is the extension for 【Pandas Basics (#202.1)】.
In this course, you will get a deep understanding of the relations between Series and DataFrame. Also, you will be able to practice more on data preprocessing with real world dataset.
Features of this course
- A recommended follow-up course after “Python Advanced (#102)” & “Numpy Basics (#201)” & “Pandas Basics (#202.1)”.
- Each row and each code will be explained in plain words.
- Free to ask any question with python or data analysis.
- Minimum number of participants: 2 people. (If there is not enough participants 5 days before the course date, this course will be cancelled.)
- The whole course will be presented in English while Chinese or Japanese questions are also available.
- ※ 講座は全部英語で進めますが、質問は日本語や中国語でも対応しております。
- ※ 本次课程内容虽为全英语授课,如有问题的话日语和中文也可以对应。
Who this course is for
- Anyone interested in learning Pandas for data preprocessing for Machine Learning & Deep Learning.
- Anyone interested about the rapidly expanding world of data science.
- Anyone who wants to explore the value of data in order to solve business problems but don’t know how to start.
- Anyone who wants to jump into AI world and becomes a data analyst.
Prerequisites
- Basic knowledge and skill for Python & Numpy & Pandas.
※ At least 6 hours programming with Python. (Control Statements, data types, etc.) ※ At least 2 hours programming with Numpy. (Arrays & Matrices Creation, Indexing & Slicing, etc.) ※ At least 2 hours programming with Pandas. (Series, DataFrame, etc.)
- Personal laptop. (Editor "Anaconda" is highly recommended.)
- Personal notebook as needed.
Agenda

Course Schedule
09:20〜09:30|Reception starts
09:30〜11:50|Course based on agenda above
11:50〜12:00|Free talk
12:00〜|Finish
※ Schedule might be slightly changed without notification in advance.
Whole Course Map

Tuition Fee
Free (無料)
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