Introduction to Deep Learning Natural Language Processing with Examples NLP with TensorFlow - From RNN to BERT

This lecture teaches various business automation methods using ChatGPT (Excel, PPT, crawling, image processing) and Python basics for business automation. Experience in advance the changed future that ChatGPT will create.

This course covers data analysis using ChatGPT and Pandas utilization. Get a preview of the changed future ChatGPT will create.

A course to learn website crawling methods using ChatGPT. Get a preview of the transformed future ChatGPT will create.

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.

We will learn step by step from the basic concepts of LLM (Large Language Model) to how to fine-tune the Llama 2 model, a high-performance LLM, on the dataset of your choice.

AI Agent: A total integration of the latest AI technology! Implement various AI agents and learn to build your own AI agent using LangGraph.

This is an all-in-one lecture where you can learn the entire process from the basics of deep learning/TensorFlow/computer vision to practical applications through a practical vehicle license plate recognition project. Through various practical exercises, you can develop practical skills to apply the latest deep learning models to custom datasets.

I'm learning how to build practical AI agents using LangGraph while working on various AI agent implementation projects using LangGraph.

This is a course to learn the concepts and usage methods of the LangChain library, and to build your own ChatGPT using the LangChain library.

This course covers work automation using MCP (Model Context Protocol) via diverse case studies: Playwright crawling, Figma design, Notion data organization, Excel data analysis.

Learn the basics of machine learning step by step through various Kaggle examples, and learn vivid project experiences and practical tips from hard-to-access field machine learning engineers all at once.

Learn all the steps from A to Z required to create and operate a cryptocurrency automatic trading coin bot. (Basics of using exchange APIs, deployment using AWS) You can also learn investment strategies (such as using Kimchi Premium) that can generate risk-free returns of around 10% per year by utilizing the structural characteristics of the cryptocurrency market.

This lecture covers building practical RAG (Retrieval-Augmented Generation) systems while developing an AI customer service chatbot (AICC).

This course teaches the process of [idea generation - data collection - verification through backtesting] for developing a Bitcoin cryptocurrency coin bot that can generate automatic profits, as well as the principles of the AIS1, AIS2 investment strategy developed by the instructor, stock selection and buying and selling points and backtesting, and the source code for bot execution.

Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.

This course teaches you how to implement deep learning papers by implementing the YOLO (You Only Look Once) paper from scratch using TensorFlow 2.0.

This is a lecture to build an AI portfolio by doing a clone project of airbnb data science team's Amenity Detection project, an excellent TensorFlow utilization case, and organizing the experience on a GitHub blog.

This lecture teaches how to create diverse quant investment strategies using ChatGPT. Use ChatGPT to build your own quant investment strategy.

Through AI company reviews, we examine how AI technology will change our present and future through various cases. By examining the necessary elements for carrying out AI projects, we prepare for the upcoming AI Transformation.

This is a lecture where you build your own MCP server using Cursor and experience vibe coding, which embodies the future of developers.

This course covers basic natural language processing techniques and various text tasks using deep learning.

We will learn step by step from the basic concepts of LLM (Large Language Model) to how to fine-tune the Llama 2 model, a high-performance LLM, on the dataset of your choice.

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.

Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

"LoRA-based lightweight fine-tuning: Your first step to creating a customized LLM!" This course is an introductory hands-on lecture designed so that even those encountering LLMs for the first time can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading models → applying data → training → comparing results. In a short time, you'll directly experience the flow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, gaining an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

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.

AI is not a technology that suddenly appeared. To properly see AI's present and future, you must understand 70 years of challenges and failures. 👉 "The moment you understand AI history, you can see both its principles and future together." Start right now!