Build an Ad-Monetized Android App with AI in Just One Day

This is a course where you can learn UML and object-oriented design even without programming experience. Concepts are explained through everyday examples (cafes, libraries, shopping malls), and you'll learn 9 types of UML diagrams step by step. You'll develop design skills that can be immediately applied in practice using theory and PlantUML.

Software development roles in the defense industry: ✔ Have different hiring criteria compared to general IT companies ✔ Use specialized tech stacks and development methodologies ✔ Offer very little information on how to effectively highlight your major, career, and projects. This course: 👉 Provides the perspective of a software developer who has experienced actual defense projects and hiring processes 👉 Explains how defense companies evaluate software developers 👉 Focuses on specific case studies to show you how to prepare your resume, interviews, and projects to increase your chances of success. This course transforms the state of "wanting to become a defense software developer but having no idea what to prepare" into a "clear roadmap you can start following right now."

I will transform the Engineer Information Processing written exam (Subjects 1–5) from a "test you solve by memorizing" into a "test where you connect clarified points directly to your score." This is an ultra-compressed lecture designed to help you grasp the entire flow within 3 days. It extracts only the core concepts repeated in past exams, structured to be understood even if viewed right before the test. The course is designed for short-term success by clearly distinguishing between frequently confusing concepts, trap points in multiple-choice options, and what needs to be memorized versus what only needs to be understood. "I'm short on time, but the scope is too broad." "I feel like I know the material when reading the book, but I keep getting the questions wrong." This lecture is for students facing these exact challenges.

This course is a hands-on program for implementing generative AI applications based on text, images, voice, and documents using the OpenAI API. Starting from setting up the Anaconda and Jupyter Notebook environment, it covers essential development environment configurations for practical work, including API Key management and understanding costs and tokens. Based on the latest Responses API, you'll implement text generation, summarization, classification, Vision (image understanding), voice processing, and PDF input processing, while practicing core features used directly in the field step-by-step, such as Function Calling, Structured Outputs (Pydantic), Embedding, and RAG (File Search). Additionally, including Web Search, Code Interpreter, Streaming, Background tasks, and Conversation State management, you'll learn how to expand beyond simple API calls to 'intelligent AI services'. Finally, the goal is to implement agent-based AI systems that autonomously select and execute tools using the Agents SDK and MCP (Model Context Protocol), while learning the structure and design perspectives necessary for actual service development.

From controlling your PC to advanced research and app development A guide to building your own 'AI work assistant' ready for immediate deployment

This course teaches you the know-how of the entire process, starting from a single idea, through planning, design, development, and up to app release on each platform. Start developing your own monetization app right now.

In the AX era where AI technology and UX design converge, what strategies should product teams use to design customer experiences? A 17-year veteran senior researcher from a major corporation and knowledge sharer with a PhD in HCI will share insights based on the latest trends, use cases, and research findings.

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

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.

This course on RAG (Retrieval-Augmented Generation) 👉 doesn't stop at conceptual explanations 👉 but involves building actual working structures hands-on 👉 and experiencing expansion and advancement through practice-focused learning. Starting from simple RAG examples, you'll progress step-by-step from Advanced RAG → Modular RAG → Agent-based RAG to a level that can be immediately applied in real-world work environments.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.

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.

# Silicon Valley Internship That Won't Get Cut Even in the AI Era & Complete Course on 30 Big Tech System Designs & Open Source Practical Contributions All students who submit course missions can apply for an AI startup internship in Palo Alto, USA, with exemption from document screening and guaranteed interview opportunities. This course involves designing and scaling 30 real-world system designs based on big tech cases including Netflix, Tesla, Meta, and Tinder. Finally, you'll design your own service from architecture → DB → scaling, contribute to an actively operating open source AI coding agent project (achieving 1.8k downloads per week) to complete your portfolio, and finalize your resume.

Jetpack Compose is Android's modern toolkit for building native UIs. Build apps quickly and vibrantly with less code, powerful tools, and intuitive Kotlin APIs.

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"! 😊

Are you confused about which technology trends really matter among the flood of information? We've analyzed global reports from Gartner, Microsoft, and others to clearly explain 10 key technologies (multi-agent systems, physical AI, AI security, etc.) that will define 2026.

You can learn everything from basic usage of generative AI to automation and creating customized AI chatbots for practical work applications all in one comprehensive course.

Now your imagination becomes the best game design document! With AI, you can complete your first game by having fun conversations as if assembling LEGO blocks. Try using Google Gemini Pro for free!

Automate Creating YouTube Shorts with AI!! Learn from scratch how to automatically create YouTube Shorts with n8n. Build a complete workflow that runs from text→image/music→video creation→upload all at once. Practice distinguishing between test mode/production mode and tips for saving costs. Complete 3 ready-to-use automation templates by the end of the course. Learn step-by-step from node placement so you can follow along even without coding knowledge. Let's automate AI YouTube Shorts production together!

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.

AI proficiency determines your salary. Leave those tedious repetitive tasks to AI 'Almost Everything About Work Automation' teaches you how to create automation systems that handle your work with just a few clicks, no coding knowledge required. You'll be freed from boring document work and data organization, and transform into an 'AI work expert' who stays ahead of others.

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.

The goal is to master the complex GPT API and Python in the easiest way possible through hands-on practice. You will develop a YouTube video summarization AI using the latest ChatGPT API and implement it as a web application using Streamlit.