Say goodbye to complicated collaboration tools! 👋 From Markdown to databases, the essential skills of a workaholic can be done with Notion 🚀

This is a Chrome Developer Tools tutorial for front-end developers. It covers various features and tips that are useful when developing.

How about starting to organize a collaboration process faster than anyone else? Google DOCS, Trello, Git... Is it possible to integrate with the tools I use? Smart way to use Slack!

You can review the basic concepts you need to know to prepare for the upcoming coding test and solve algorithm problems using Python and Javascript.

How to Build an Efficient Startup Workflow System with Just Notion 🧑🏻‍💻 (Practical Workflow Templates Provided by Practitioners)

Anyone can learn data analysis with Chat GPT. You can learn how to apply it in practice through various analysis exercises. (Absolutely!! ChatGPT paid version is required!)

No more toy projects! We're revealing all the secrets to building a secure authentication system with JWT and Redis, actually used by developers in the field.

Playbot is an educational SW that makes it easier for students to learn SW using Javascript or Python. Here, we will help you learn what you can do with SW and develop computational thinking skills through simple practice. (The language used here is Javascript)

New to both Blender 3D and 3D in general? A 3D KakaoTalk emoticon creator will directly teach you in this beginner-friendly 3D introductory course.

This class is for anyone who wants to become a SW instructor and provides a curriculum, materials, and the know-how and tips from a 15-year veteran instructor.

Python Basecamp is a course for beginners who want to learn the basic concepts of Python. Improve your skills through basic concepts and practical examples.

PyGame, a game made with Python! Let's make a fun game with Winnie the Pooh!

I hope that through this course you will gain a clearer understanding of grammar and gain confidence in solving problems.

I hope that through this course you will gain a clearer understanding of grammar and gain confidence in solving problems.

Let's create a Jeju Olleum map guide service using public data and Folium! It's not a service that only I can see, but a service that others can access! It's not a portfolio that I have as a file, but a service that others can access!

Learn the basic concepts of Three.js and apply them to carry out a mini project called 'Building My Own Island'. You can learn Three.js easily and lightly while carrying out the project.

Learn how to use Notion, from the basics to creating templates, in just one course!

King Basic🐥, only for those who say they have no more words to describe me.👂 Concepts go to the universe🚀, King Basic practice day and night✍, learn SQL with your hands!✋ No installation required.🔥 Here is the lecture restaurant, Jecobe!🎉

An amazing lecture that will make you understand regular expressions just by listening! Don't give up! Don't put it off! Come on, let's do it now!

Know! Well! Just! Neatly! Sensefully! This is a free lecture on the GitHub core concept book. You can download the book and Notion link for free. It is a non-profit project, so using the textbook is allowed without permission.

This is a lecture for perfectly understanding the process of training the simplest form of deep learning model using gradient descent.

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

We have prepared video lectures so that more people can understand machine learning and deep learning and solve their own problems using these great tools. Furthermore, we have not only covered the theory, but also implemented the theory using TensorFlow, an open source for machine learning recently released by Google.

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

This course is an introductory program designed so that learners who are new to AI technology can easily understand and follow along. Through the lectures, you will learn the basic concepts and usage methods of AI platforms, and conduct hands-on practice directly generating images using various AI tools. Upon completing this course, you will become much closer to AI and acquire the capability to create AI images that can visually implement creative ideas.

The PyTorch_Project Edition, understood instantly with code, implements practical deep learning projects using image, video, and NLP data, understanding model structure and flow through code-centric learning over theory.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

This course explains the basic concepts of LLM and GPT in an easy-to-understand way for everyone. Students can directly use the GPT API to create chatbots and run them on the web using Streamlit. By experiencing everything from basics to hands-on practice, you can solidly establish your first steps in AI utilization.

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

From the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

Essential certification for the AI era, MS AI-900! 🚀 Did you know? ChatGPT operates exclusively on Microsoft Azure! If you want to properly utilize Microsoft Azure OpenAI, which exclusively provides the latest GPT models, now is the perfect opportunity. Grow into an Azure AI services expert through the AI-900 course and master enterprise-grade AI solutions that companies trust. Secure global official certification and enhance your competitiveness as a true AI professional!

This course is a hands-on masterclass that completely dissects the core technological evolution of generative AI, from LDM (Latent Diffusion Model) to DiT (Diffusion Transformer). We directly analyze the latent space-based learning principles of LDM, the structure of Stable Diffusion, and the implementation methods of the latest Diffusion Transformer through papers and code. Students will systematically learn the latest trends and structural evolution of generative models by directly implementing LDM, CFG (Classifier-Free Guidance), and DiT models using PyTorch.

This course is a comprehensive program that covers everything you need to know to utilize generative AI in practical work settings, from the basic principles of LLM (Large Language Models) to RAG (Retrieval-Augmented Generation), and even the latest technologies like AI Agent and MCP (Modular Command Protocol). It is structured to naturally teach you how generative AI understands, searches, judges information, and extends into AI Agents that take action, following the flow of technological development.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

If you want to be recognized as a machine learning expert based on large-scale data, from understanding the core framework of Spark machine learning, to SQL-based data processing through difficult practical problems, to data analysis through business domain analysis, and to the ability to implement optimized machine learning models, please join this course.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

This course starts with the question "If I had been on the Titanic, could I have survived?" and completes a full-stack project that develops an AI model to predict survival probability based on actual data and serves it as a web service. You'll practice the entire process of AI and web development, from deep learning modeling using PyTorch, building a backend server with FastAPI, to implementing a user interface with Next.js.

Through this course, students will learn various reinforcement learning theories and implement them themselves, as well as create a reinforcement learning environment to test the reinforcement learning algorithm implemented using Unity Machine Learning Agents.

From Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder based MarianMT translation model, and even Vision Transformer, you'll learn Transformer inside and out by implementing them directly in code.