Introduction to Programming in Numpy (#201)

• What is Numpy?
• How to use Numpy for matrix operation.
• 10+ Numpy functions with 3 practical examples.

About this course

Numpy is a library for the python programming language. It is famous for large, multi-dimensional arrays and matrices calculation, along with a large collection of high-level mathematical functions to operate on these arrays.

In this course, you will get a fully understand about what is Numpy, why it is required in data analysis and how to use Numpy from scratch.

Furthermore, for those who want to take a further step for machine learning and deep learning, Numpy is an imperative package before going any deeper.

Features of this course

1. A recommended follow-up course after “Python Advanced”.
2. Each row and each code will be explained in plain words.
3. Free to ask any question with python or data analysis.
4. Minimum number of participants: 2 people. (If there is not enough participants 5 days before the course date, this course will be cancelled.)
5. 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

1. Anyone interested in learning Numpy for data preprocessing for Machine Learning & Deep Learning.
2. Anyone interested about the rapidly expanding world of data science.
3. Anyone who wants to explore the value of data in order to solve business problems but don’t know how to start.
4. Anyone who wants to jump into AI world and becomes a data analyst.

Prerequisites

• Basic knowledge and skill for python.

※ At least 6 hours programming with python. (Control Statements, data types, etc.)

• Personal laptop. (Editor "Anaconda" is highly recommended.)
• Personal notebook as needed.

Agenda

1. Numpy Introduction
2. Arrays and Scalars
3. Indexing and Slicing
4. Array Processing
5. 3 practical examples

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)