Python Basics for Beginners

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

Knowledge Graph-based RAG System Implemented with Neo4J: Next-Generation Search Technology Utilizing Data Relationships Beyond Simple Vector Search Maximizing RAG Performance with the Power of Graph Databases!

Learn LangChain's basic concepts and usage with Python. Hands-on practice will be conducted primarily in a Google Colab (colab) environment, with materials provided via Github.

Building a Retrieval-Augmented Generation (RAG) Intelligent AI Agent with LangGraph! From theory to practice, this is a hands-on tutorial that even beginners can easily follow.

This course is designed for beginners and consists of easy explanations and various hands-on projects. It covers data collection using web crawling and LangChain tools, and summarization, extraction, sentiment analysis, and recommendation systems using LLM.

Create your own AI chatbot using Python's basic syntax and libraries. Learn through a step-by-step process of completing 5 projects, including PDF document-based RAG, and deploy them as web services.

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

I want to do data analysis and machine learning with Python programs. Isn't it difficult? First, you need to learn the basic grammar and basics of Python programs. This course will help you get out of the beginner stage.

Introduces the main concepts and basic grammar of the programming language Python. This is a comfortable and friendly lecture that even beginners with no related knowledge can understand.

This course will help you quickly learn the core concepts of Python and the Pandas library. Improve your programming skills by solving the practice problems at the end of each part!

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

Solve coding test problems using Python.

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.

You will learn techniques that can be applied in various fields of IT security, starting from the introduction to Python programming.

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

This is a Python course provided by shop2world.

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

Many Python learners understand basic syntax but struggle because they lack the algorithmic thinking and implementation skills needed to solve real-world problems. In this course, you will learn by directly implementing 12 core algorithms frequently used in development and data processing using Python. We have structured the course to go beyond simple theoretical explanations, allowing you to gain a deep understanding of how algorithms work through actual coding and debugging processes. The course provides step-by-step explanations of algorithms that frequently appear in practical work and problem-solving—such as sum, average, max/min, sorting, searching, merging, and mode—and guides you through implementing them in Python code. If you are a learner aiming to become a Python developer or data analyst, you can simultaneously improve your algorithmic thinking and code implementation skills.

A course where you can create programs for running a blog using Python and generate additional income through sales and branding.

Learn about the basics of Python required for data analysis, the data analysis framework (pandas), and the data analysis process.

Do you manually type in numerous commands every time you build a complex project or create a deployment package? Currently, most open-source projects use build automation scripts to save the trouble of typing commands. Do you also find building tedious? Then use this course to automate your builds and increase your work efficiency.

Learn Python coding. Learn design scripting with Rhino3d Grasshopper. Learn creative coding such as computational thinking, parametric, and generative design.

You can easily and enjoyably understand Python programming with games. This is a lecture that even children in elementary and middle school can follow, so parents and teachers will find many places to use it if they learn it. :)

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

"Automating your work? Who doesn't know what's good for them?" You don't need to use a knife to catch a chicken. I want to show you that 10 lines of simple code are more practical than complex crawlers on the Internet.