|先着順||無料||3人 ／ 定員4人|
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
- A recommended follow-up course after “Python Advanced”.
- 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 Numpy 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.
- 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.
- Numpy Introduction
- Arrays and Scalars
- Indexing and Slicing
- Array Processing
- 3 practical examples
09:30〜11:50|Course based on agenda above
※ Schedule might be slightly changed without notification in advance.
Whole Course Map