Tác nhân AI tự động hóa công việc sử dụng ngay tại công ty (w. n8n, LangGraph)

RAG. Learn from Silicon Valley GenAI Hackathon Winner. Packed with real-world know-how.

LangGraph, packed with a major corporation's AI Agent lead's know-how. We deliver knowledge gained from real-world challenges.

This is a basic LangChain lecture that extracts the key points from official documents for the price of a cup of coffee. Get familiar with LangChain grammar before you start developing!

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

How to Use Storybooks A to Z. We show you everything about storybooks.

Test code! For those who are at a loss as to where to start, here it is. From writing tests to deploying through automation, all in one place!

This is for those who want to deploy/operate services with AWS. From domain settings to Docker and serverless!

A Complete Guide to Building an AI Chatbot System with Langchain and RAG! Provides a systematic learning process for generative AI development technology.

LangGraph, packed with a major corporation's AI Agent lead's know-how. We deliver knowledge gained from real-world challenges.

This course is designed to simultaneously develop both fundamental theory and practical application skills needed to proficiently execute AI modeling projects in real-world settings. Learners will understand the overall flow of AI projects and experience step-by-step processes through hands-on practice: problem definition → model design → data acquisition and preprocessing → feature extraction → model training and validation. Additionally, by learning how to select and manage optimal AI models in various situations, learners can build practical AI capabilities that can be applied to actual business environments. Through this course, learners can systematically understand the entire AI modeling project process and strengthen their data-driven problem-solving abilities based on this foundation.

The AWS Certified AI Practitioner practice exam problem-solving course is a core summary course for certification success. First, you will quickly review the basic concepts of AI/ML and generative AI, and learn the functionalities and use cases of key AWS AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you will practice determining which AI solution is suitable for various real-world problem situations, and also cover topics related to the responsible use of AI models and data security. Finally, you will learn problem-solving strategies for each type of past exam question and prepare for the exam through practical mock tests. Through this course, you can efficiently prepare for the exam in a short period.

AI Utilization Master Guide for Java Developers! This course breaks the stereotype that AI is exclusive to Python, and grants your Java apps AI's eyes, ears, voice, and coding abilities. Grow into an AI architect based on OpenAI API. Directly develop various AI specialists such as AI writers, translators, artists, and coding partners, and create a multifunctional AI assistant that integrates core features like text summarization, sentiment analysis, image description, Java code generation, voice/text conversion, and image/subtitle generation. Learn to assign roles to AI through system messages and even content moderation for harmful content - this is a golden opportunity to maximize the competitiveness of your existing Java systems.

Leverage Python to learn machine learning techniques, improving real data information extraction and prediction model development skills!

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

AI writes on my Slack and Notion for me? Work smarter with MCP that surpasses the limitations of existing AI!

PyTorch Fundamentals: Code-Based Clarity is a complete guide for anyone wanting to implement deep learning models using PyTorch, from deep learning beginners to developers aiming for practical application. Through 19 systematic lectures, you can perfectly master the core of deep learning, including PyTorch basics, deep learning algorithm implementation, overfitting problem resolution, and even CNN, RNN, GAN models.

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.

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will comprehensively learn everything from establishing AI-based system test strategies to designing and executing test cases, and even methods for utilizing AI to support testing. This course is conducted based on ISTQB's AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

Explains the basic principles of large language models like ChatGPT, focusing on theory.

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

An introductory AI lecture tailored for those new to AI! Key concepts, from data to generative AI, are simply explained. The goal is practical understanding, enabling you to question and explain AI, not build it.

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

Do you still code directly these days? It's now an era where even vibe coding is bothersome! Become an AI automation expert with n8n, without coding. An automation workflow design guide immediately applicable to practical work. Practice-oriented automation strategies that maximize work efficiency. Build intuitive workflows with n8n and experience business innovation.

Create high-quality AI videos with Midjourney&Runway. Director Kim Dong-ah, who collaborated with Samsung, will personally guide you step-by-step through the AI video production process based on a virtual brand.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

"An introductory hands-on course for creating domain-specific customized LLMs with LoRA-based lightweight fine-tuning!" You can now create customized LLMs yourself. This course is designed to help you easily learn the process of creating domain-specific LLMs through LoRA-based lightweight fine-tuning practice, without complex theory. Even those handling LLMs for the first time can follow along, as we guide you step-by-step through the entire process: loading models → inputting data → training → comparing results. Learn the latest techniques for creating LLMs specialized in specific fields with minimal resources through direct hands-on practice!

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 :)