Full-stack Voice-to-Text AI Note Web App with WhisperX: From Development to Monetization with a Payment System

This course covers the fundamentals of the Notion API and teaches you how to automate Notion by integrating AI (Claude) using Notion MCP. You'll learn to directly control blocks, pages, and databases by following the official API documentation, and ultimately complete a hands-on project that creates databases and automatically adds pages by analyzing text file content using only natural language commands (prompts).

This is a practical course where you can learn the process of building a company website yourself using React, Node.js, and MongoDB. Let's build a full-stack project together with a basic background in React and Node.js!

What if AI could directly open a browser and write shell scripts to resolve server issues? Through practical automation know-how implemented with OpenClaw across Windows and Linux, we guide you on the shortest path to completing your own powerful remote development environment without complex configurations.

Build a zero-cost pipeline by installing ComfyUI on Kaggle's free GPU, connecting via Pinggy tunneling, and linking it with n8n workflows to automatically iterate through Google Sheets prompts for bulk image generation, storage, and notifications. Through 10 chapters over 8 hours, you will practice everything from the ComfyUI node system to REST API conversion and n8n Loop/Webhook integration, reproducing the same results using provided JSON files. Even without programming experience, you will complete a practical automation factory that mass-produces SNS, advertisement, and thumbnail images unattended.

Do you want to automate repetitive tasks with AI without using paid tools? I will share the practical know-how I gained from building systems myself using n8n and Llama. This is not a lecture where you simply learn "how to connect nodes." We will build actual workflows that you can use immediately, such as automatic Google Sheets organization, YouTube subtitle collection, AI fact-checking, and schedule management.

Based on the experience of wondering how facial recognition works in offline environments on-site, this course will guide you through building the basic structure of a facial recognition-based access and attendance management system using React + Electron and Python's FastAPI-based DeepFace. Rather than focusing on perfection, we focus on understanding the operating principles and laying the foundation for you to expand into your own personal projects.

Starting with the question, "If I were on the Titanic, would I have survived?", this course completes a full-stack project where you develop an AI model to predict survival probabilities based on real data and deploy it as a web service. You will gain hands-on experience in the entire process of AI and web development, from deep learning modeling using PyTorch to building a backend server with FastAPI and implementing a user interface with Next.js.

This is a practical course where you will directly create a timer app using React, Electron, and Zustand, and even deploy it to cross-platforms (Windows, macOS, Linux). Starting with familiar React web development, you can learn the entire flow of desktop app development, including global state management via Zustand and final GUI deployment!

In this course, we will practice step-by-step how to use React and FastAPI to implement social features such as real-time voting, comments, and likes, as well as how to monetize by integrating payment systems (Kakao Pay, Toss Pay, etc.).

🔥 Building a customized platform for learning Chinese characters! Utilize Google Gemini AI and Firestore to implement your own Chinese character vocabulary list, stroke order animations, and even handwriting recognition!

🔥 Firebase User Authentication Completed with just HTML + Tailwind CSS + Pure JavaScript! From social login to phone and location verification, easily and quickly build an account system without a complex backend.

This is a profit-oriented practical course where you will directly develop coin/stock automated trading systems and apply real-world trading strategies such as Grid, Moving Average, and Martingale. You will build 24-hour automated trading bots through practical trading exercises using Upbit, Binance, and Korea Investment & Securities (Kiwoom Securities) APIs, along with cloud deployment, while exploring real-world strategies for monetization. #Quant #Bitcoin #Algorithm #Investment #WealthManagement #AutomatedTrading #Bot #Agent #AI #OpenClaude #ClaudeCode

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

New to Flutter? A Flutter Contributor will guide you step-by-step! Start Flutter dev with an AI project using Gemini.

Starting with the question, "If I were on the Titanic, would I have survived?", this course completes a full-stack project where you develop an AI model to predict survival probabilities based on real data and deploy it as a web service. You will gain hands-on experience in the entire process of AI and web development, from deep learning modeling using PyTorch to building a backend server with FastAPI and implementing a user interface with Next.js.

Python Korean Text Analysis and Natural Language Processing: Word Cloud Visualization, Morphological Analysis, Topic Modeling, Clustering, Similarity Analysis, Bag of Words and TF-IDF for Text Data Vectorization, Text Classification Using Machine Learning and Deep Learning, and How to Use Hugging Face

Using the ChatGPT API, develop a full-stack multilingual translator web application in just 30 minutes, and even if you know nothing about AI, try incorporating the latest AI (ChatGPT API) into your product!

Practical Payment System Development Course, learn by code, and cover the knowledge needed to implement a real system.

Let's implement a web service modeled after Pinterest's unique card-type layout design using Django, Python's representative web framework.

Are you having trouble integrating payments into your web service? Quickly apply payments to your service using Django and I'mport.

The "How Far Can You Go with ChatGPT?" series: Creating a Stock Auto-Trading Application and Web Investment Reports!

We implement the latest Transformer-based PixArt and lightweight adaptation SANA step by step from theory to code. Building on DDPM·DDIM·LDM·DiT covered in Parts I·II, we complete hands-on practice including text encoder integration, samplers (DDIM/ODE), v-prediction/CFG tuning, and small-scale data style fine-tuning.

The era of Physical AI, as mentioned by Jensen Huang in 2025, is coming—alongside Perception AI, Generative AI, and Agentic AI. Experience Physical AI firsthand, quickly and easily. Explore Physical AI using Hugging Face's LeRobot library and actual physical robots.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

This course explains the basic concepts of LLM and GPT in an easy-to-understand way for everyone. Students will build their own chatbot using the GPT API and deploy it on the web using Streamlit. By experiencing everything from the basics to hands-on practice, you can build a solid foundation for your first steps in utilizing AI.

Learn how to start developing a web app project using Django (2.0 or later), and use the content to create a simple non-member bulletin board site that can be run on AWS.

We understand why Attention was needed and how it works by 'implementing it directly with code'. This lecture starts from the structural limitations of RNN and Seq2Seq models, experimentally verifies the information bottleneck problem and long-term dependency issues created by fixed context vectors, and naturally explains how Attention emerged to solve these limitations. Rather than simply introducing concepts, we directly confirm RNN's structural limitations and Seq2Seq's information bottleneck problems through experiments, and implement **Bahdanau Attention (additive attention)** and **Luong Attention (dot-product attention)** one by one to clearly understand their differences. Each attention mechanism forms Query–Key–Value relationships in what way, has what mathematical and intuitive differences in the weight calculation process, and why it inevitably led to later models naturally connects to their characteristics and evolutionary flow. We learn how Attention views sentences and words, and how each word receives importance weighting to integrate information in a form where formula → intuition → code → experiment are connected as one. This lecture is a process of building 'foundational strength' to properly understand Transformers, helping you deeply understand why the concept of Attention was revolutionary, and why all subsequent state-of-the-art NLP models (Transformer, BERT, GPT, etc.) adopt Attention as a core component. This lecture is optimized for learners who want to embody the flow from RNN → Seq2Seq → Attention not through concepts but through code and experiments.

This course delves deeper into the program or file structures that we take for granted or commonly encounter, using Python.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

★PYTHON★ This is a basic lecture on server development using Fast API. Learn how to develop servers easily, quickly, and conveniently using various packages such as Fast API, SQLAlchemy, Pydantic, and Starlette! Don't worry, we have prepared a DB backup file as well as integration with PostgreSQL! We will teach you the "basics" of UI design using Dash and Plotly and provide the source code used in the lecture :)

Digital marketing that makes money, such as Naver Shopping and Coupang Partners, requires consistency, but you can approach it easily and effectively with scientific analysis and automation. We will teach you the key secrets of creating a program that collects and analyzes popular products, keywords, blogs, and shopping information.