You don't have to say "summarize this" every time. In this lecture, you will learn how to create your own AI agent in Antigravity and use it immediately without repetitive explanations. The course is practice-oriented so that even beginners can follow along. https://antigravity.google/download (You can download the Antigravity Editor here :))

We will directly implement an AI web service integrated with the OpenAI API using only HTML, CSS, and JavaScript. By utilizing Netlify Functions, we will securely protect the API key and proceed with actual deployment using a static frontend + serverless backend architecture. This is not just a simple demo; we will complete a monetizable MVP from start to finish through a live IDE session.

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.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for seniors (60+) who are vulnerable to AI adoption. *Priority for people with disabilities Are you curious about AI but unsure how to get started? This course is an introductory program designed to help seniors start learning AI comfortably and enjoyably. Join instructor Choi Jin-young to create text, images, and even videos using AI tools like Wrtn!

See exam types and trends at a glance! Strengthen your practical skills with approximately 100 questions. The perfect preparation for the AWS AI Practitioner exam, allowing for systematic study even when preparing on your own.

It’s okay if you don’t know how to code. This course focuses on the experience of using AI to build an ad-revenue-generating Android app from scratch and successfully launching it in just one day. Many people stop at these stages: “I built the app, but how do I monetize it?” “I tried adding ads but got stuck on AdMob, policies, and reviews.” “I gave up right before launch because of the privacy policy.” In this course, we will navigate through every "drop-off point": 👉 Idea → App Creation → Ad Integration → Store Launch Essentials → Actual Deployment. We let the AI do the work, and we make the decisions. The goal is to complete an app with a "functioning revenue structure" within a single day.

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!

The most rapidly emerging task automation tool recently is 'Claude Code.' Through Claude Code, you can deploy AI agents within your computer that work exclusively for you and create a system where repetitive tasks are assigned to the AI one by one. Try automating 100% of the once-exhausting tasks like PPTs, reports, and Excel work.

Innovation in Work Efficiency and Creativity – Agentic AI AI is now evolving beyond simple automation into a new stage where it can judge and execute on its own. Agentic AI is at the center of this change, serving as a core technology that helps businesses and organizations operate smarter. In this course, we have organized the content clearly and simply so you can understand how Agentic AI connects decision-making with execution and how it can be applied to practical work. Discover the essential knowledge for every professional preparing for the future right now.

You don't have to say "summarize this" every time. In this lecture, you will learn how to create your own AI agent in Antigravity and use it immediately without repetitive explanations. The course is practice-oriented so that even beginners can follow along. https://antigravity.google/download (You can download the Antigravity Editor here :))

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

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 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.

AI Work Automation + Side Income Generation with Just One Click!!! Make, the ultimate work automation tool - have you been hesitating to start due to its complex settings and features? Build the automation you've been dreaming of with step-by-step lectures that even beginners can easily follow.

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.

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.

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

The real story of an AI-native company run by GolbinHacker, the 1st place winner of Kakao AI TOP 100 and author of the bestseller "The Best Prompt Engineering Lecture." It explores how just two developers build and operate a service, along with the new competencies developers and organizations need in the AI era through real-world cases.

AI is no longer a tool exclusive to developers or experts. The gap between "those who use AI" and "those who don't" is already widening across all roles—from students and job seekers to office workers, planners, and developers. This course is a practical survival guide focused on: ✔️ How to use AI as a tool to explode your productivity, not as a replacement technology ✔️ Prompts you can immediately apply to work, studies, job hunting, planning, and development ✔️ The mindset that turns someone who says "I tried AI, but it wasn't that great" into an AI expert Rather than just explaining features, I will show you: 👉 What kind of people survive in the AI era 👉 Exactly how those people use AI in practice Based on my own experiences and real-world examples.

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.

This is a hands-on tutorial on how to integrate with IntelliJ and develop quickly using the Model Context Protocol (MCP).

You can learn the core concepts of complex Next.js in a short time. We'll teach you only the essential practical knowledge for those learning Next.js for the first time. Captain Pangyo's new Next.js course, who has been conducting framework courses for 8 years. You can learn the coding and learning methods of "Frontend Developers in the AI Era"! 😊