Python with Jupyter Notebook

Using jupyter notebook
Learn the basics of using pyhon 📚

I used a program called MATLAB until I was a student, and then I started learning Python after I graduated. Many people said Python was easy, but I felt a strange sense of resistance to it. Although it was easy, there were many parts that were different from the MATLAB I used, so I had a hard time. As time passed and I became familiar with Python, I made the 'Python lecture like MATLAB' that I made last year based on my memories. However, that lecture was too focused on me, so I made a popular introductory lecture this time. The part that I worried the most was who it would be for. There are already many lectures and books on the market, so I didn't think I needed to make a lecture. So I made an introductory lecture that was fast-paced for those who have already been exposed to programming. Instead of the friendly explanations provided in many introductory Python lectures, I tried to increase the speed of the lecture by providing quick explanations through examples. So I hope that many people will listen to the lecture without any inconvenience. Thank you.

📍 Course Introduction

_{The jupyter notebook files used in the lecture are provided in compressed file format.}

Through this lecture, you can learn python and jupyter notebook. It takes a lot of effort and time to learn something. In this lecture, you can see the results of the code right away through jupyter notebook, and the parts that are deemed unnecessary at the introductory stage are boldly omitted to help you learn a little faster. After completing this lecture, I think it will be of some help to learn python, which you were reluctant to learn.

Section 0. Introduction to the Course

The lecture introduction section introduces the content of the lecture and the students who recommend the lecture, and includes instructions on how to install and run Jupyter Notebook.

Section 1. Data Types

Contains explanations of data types supported by Python (numbers, characters, lists, tuples, dictionaries, and sets).

Section 2. Control Statements

It contains explanations about loops (for, while) and conditional statements (if).

Section 3. Functions

I have summarized how to create functions using def and how to use them.

Section 4. Exception Handling

We introduced exception handling used when an error occurs.

Section 5. Using the Library

I have introduced how to install and use external libraries.

Section 6. Appendix

A brief explanation of the markdown supported in Jupyter Notebook.

✨ Expected Questions Q&A

Q-1. Can non-majors also take the course?
A-1. It is possible. However, since my target audience is people who have basic programming language experience, there may be some parts where the explanation is lacking.

Q-2. Is there anything I need to prepare before attending the lecture?
A-2. As explained in the introduction, you must install Anaconda and create an environment where Jupyter notebook can be used.

Q-3. To what extent does the class cover the content?
A-3. It covers the basics of Python, but it omits classes that are usually introduced in books or lectures to increase the speed of the lecture.

🙋‍♂️ Why I created this course

Korean and English are the same language, but just because you can speak Korean doesn't mean you can easily learn English. Learning English requires a lot of effort. I think programming languages are similar. Although they are the same programming languages, learning a different language requires time and effort. In this lecture, we put a lot of thought into lowering the hurdle of time and effort for learners.

Introducing the knowledge sharer

Over the past three years, I have created several lectures on Inflearn, and over 3,000 people have taken my lectures and responded well.

_{Inflearn Knowledge Sharer Blog}

Knowledge Sharer Other Lectures

PYTHON like MATLAB