初心者のための簡単なPythonの基礎とデータ分析

For beginners, learn about the most basic commands of git & github, flow.

This course is designed to teach the basics of the Python programming language in an easy and practical way that suits modern life. Python is easy to learn even for beginners thanks to its concise and easy-to-read syntax, and is used in various fields such as data analysis, web development, and artificial intelligence.

This course is a direct lecture by the author based on the book "Python Quick Start - Python for Work - Ruby Paper (2023/04)". This course is a course to learn the basics and usage of Python, which is known to be easy to learn, so that even non-majors can use programming in real life or work. You will learn Python programming methods through real business cases rather than grammar-centered ones, and you will be able to increase the efficiency and reliability of your work by automating various business processes including HR and finance.

Data analysis sounds a bit grandiose, but it is actually a process of establishing a hypothesis and verifying it based on data. You can learn how to analyze what data to verify your hypothesis using Python.

This introductory course, designed to be the easiest and most practical for Python beginners, covers intuitive dashboards using Streamlit, Google Cloud Platform for deployment, and more. Additionally, you can also prepare for the 빅데이터 분석기사 practical exam.

This is a basic DFS lecture that explains the way a liberal arts major and working developer studied to get a job :) We have prepared a lecture where you can learn by solving problems yourself, with minimal boring theory lectures! After taking this lecture, you will be able to solve silver level DFS problems on your own according to Baekjoon standards.

Learn NoSQL technology, which can handle Big Data, one of the fundamental technologies in full-stack and data science utilized by modern startups. MongoDB is the easiest and quickest technology to utilize among NoSQL databases. In this lecture, you will learn the basics of MongoDB in a short time, and also acquire the skills to manipulate and utilize MongoDB with Python.

Let's build a foundation for using Python and solve data analysis problems!

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

In this course, you will learn how to program kernels and develop PyTorch modules. You can use the knowledge you have gained to develop models faster.

How to easily set up git, VS Code, Node.js, Python, Java dev environments on Windows within 2 hours without struggling.

We will develop a web app that collects data using concurrent/parallel programming in Python, loads it into MongoDB, analyzes it, and visualizes the collected data using FastAPI, a modern web framework. In the process, you will learn and understand Python concurrent/parallel programming using coroutines, multi-threading, and multi-processing, and understand how to use them to improve Python's performance. We will help you apply Python concurrent/parallel codes directly to your work. We will not only teach you how to develop and end, but also how to deploy and operate an actual app on the AWS cloud.

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

A course where you can not only build programs required for blog operation using Python, but also earn additional revenue through sales and branding.

Anyone can easily create a Python game using the Pygame library, starting from zero base.

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

This is a Python coding test lecture centered on problem solving, tailored to those who are new to coding tests.

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

Learn network programming from scratch, fully utilizing Python and ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly writing network code through practical exercises and personally verifying how their written programs operate. You can acquire skills ranging from basic network practicals to network technologies applicable in real-world scenarios, and build deep understanding and proficiency through exercises dealing with various protocols and tools. Furthermore, by leveraging ChatGPT, students can have a memorable learning experience without feeling difficulty or boredom.

If you are planning a service, a website is an essential element. Of course, in addition to the service, most of the currently provided program infrastructures operate based on the web. The purpose of this course is to learn how to create a website using Python, which is considered the easiest programming language, and how to set it up to an actual operational state.

Prepare perfectly for the Programmers Coding Essential Competency Certification (PCCE), from Python basics to competency certification!