This course covers the entire process of designing and implementing generative AI services centered on LangChain 1.0 and LangGraph through step-by-step hands-on practice. Beyond simple LLM calls, you'll directly implement operational AI system architectures that include agent-based architecture, state management, memory, streaming, middleware, and Human-in-the-Loop. Through hands-on practice with document/PDF/web data-based RAG systems, SQL Agent (Chinook DB), tool-calling-based Agents, Supervisor pattern multi-agents, and state machine-based workflows using LangGraph Graph API, you'll build reusable agent pipelines that can be immediately applied in real-world scenarios. Additionally, through structured output (Pydantic-based), agent middleware (Summarization, HITL, Retry, PII protection), and token/step-by-step streaming, you'll complete generative AI applications with the stability, scalability, and controllability required in actual services. 👉 For those who want to accurately understand the internal structure and execution flow of LangChain/LangGraph 👉 For those who want to implement RAG·Agent as a real service structure, not just a "demo" 👉 This is the optimal course for those who need a realistic practical roadmap covering state-based agents, SQL·document automation, and multi-agent orchestration.

As AI rapidly permeates daily life and industries, attack techniques targeting these systems are evolving alongside them. This course is a practical, hands-on program designed to help you understand the latest security threats surrounding Generative AI and LLMs, automate security tasks using AI, and experience LLM jailbreak attacks and defenses firsthand.

We will summarize all the hot topics regarding Generative AI, LLMs, and Agents from throughout 2025! Focusing on the announcements from the three major AI developers (OpenAI, Google, and Anthropic), we will take a look at the trends of AI that have advanced remarkably in '25.

This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for job seekers who are vulnerable to AI. Career expert Career D will teach you step-by-step how to apply AI to job searching and career transitions. From basics to hands-on practice, it's designed so that even AI beginners can follow along easily without any burden!

The AWS Certified AI Practitioner practice exam course is a core summary program for passing the certification. First, you'll quickly review the fundamental concepts of AI/ML and generative AI, and learn about the features and use cases of AWS's major AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you'll practice determining which AI solutions are appropriate for various real-world problem scenarios, and also cover content related to responsible use of AI models and data security. Finally, you'll learn problem-solving strategies by question type and prepare for the exam through practice mock tests. Through this course, you can efficiently prepare for the exam in a short amount of time.

We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

Learn how to utilize various local LLMs (Qwen, Gemma) and explore different techniques to efficiently evaluate and improve the performance of LLM systems.

This course is designed for those who use AI but are confused about how much they can trust it. It covers how to use AI in your work or creative process without overdoing it, ensuring it provides actual value. Rather than requiring professional development knowledge or complex tools, it focuses on how anyone can effectively integrate AI into their own workflow. Instead of teaching complex prompt engineering, the course focuses on the mindset of **knowing when to use AI and when it's better not to**, as well as **how to verify and refine AI outputs** rather than trusting them blindly. Through this course, you will establish criteria for using AI not as an automation tool that replaces everything, but as a **practical partner** that helps organize your thoughts and assists in your work.

As AI systems become agentic and expand beyond text into image, audio, and multimodal capabilities, security threats are becoming significantly more complex. This lecture analyzes the latest security threats and attack techniques faced by AI Agents and Multimodal LLMs, as well as real-world cases, from an AI Red Teaming perspective.

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 will not replace people. People who master AI will replace those who rely on it." In the era of AI, where creating results has become easier than ever, human thinking and problem-solving skills are becoming even more critical. Jae-sung Kim, a former McKinsey consultant, will guide you step-by-step through advanced problem-solving skills using AI, powerful research strategies, and persuasion techniques to turn your results into reality.

Navigate the data ocean, explore AI's future. This course explores the vast tech currents of Big Data and AI, examining their innovation in our lives and work.

"In such a busy world, you can create a portfolio quickly using AI?" From problem definition to research synthesis, ideation, and prototyping! Use AI as your practical partner to quickly build a high-quality UX/UI portfolio. You can strategically utilize not only the latest AI tools but also proven tools consistently used in the industry to fit your project.

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

It explains the fundamental principles of large language models like ChatGPT, focusing on theory.

You use ChatGPT, but haven't you found it difficult to explain why it gives certain answers? "I know terms like RAG, Agents, and Fine-tuning... but it's hard to explain them accurately." "I get tongue-tied whenever I hear LLM-related terminology." "Conceptual explanations are always vague during AI meetings." This course was created specifically for people like you. This is a theoretical course designed to help you understand LLMs not just as a 'tool,' but as a 'structure.' It doesn't teach you how to use ChatGPT or Gemini; instead, it establishes the foundation so you can explain exactly why they work the way they do.

The era of simply receiving code "suggestions" is over. I will clearly and simply introduce you to Google Antigravity, a next-generation agent development platform where AI agents directly control the editor, terminal, and browser to plan, execute, and verify complex software tasks.

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.

Reading the Standard of Digital Money — A New Financial Order Opened by Stablecoins In the uncertain digital asset market, stablecoins—the only assets that function "like real money"—have already emerged as a core part of the global financial infrastructure. This provides essential, condensed knowledge for professionals who want to be at the forefront of understanding the paradigm shift in the digital economy.