Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma

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

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 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 will teach you the core theories of deep learning and how to implement deep learning code using the latest TensorFlow 2.0.

Non-Majors Welcome: Real-World Vibe Coding Projects Created Through Conversations with AI

Learn context engineering techniques for creating high-quality AI agents through hands-on practice.

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

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

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

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

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

This is a lecture on creating an automatic stock trading bot using the IBK Investment & Securities Xing API. Create your own automatic stock trading bot that trades automatically 365 days a year.

A course to learn website crawling methods using ChatGPT. Get a preview of the transformed future 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 deep learning paper implementation skills, implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper from scratch with TensorFlow 2.0.

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

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.

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

LLM: A pro quickly delivers core content, from essentials to practical tips!

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 is a course to master the fundamental theories of LLM and the core technologies of LangChain and RAG. You can easily learn the latest AI technologies used in practice, starting from LLM basics!

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

Explains the reasons why LLM is necessary, the technical background, and basic concepts for LLM planners and LLM application planning managers.

A course that will teach you how to create a website with ChatGPT and take charge of its distribution! Learn even fine-tuning.

Learn the entire process of running the latest Gemma 4 model directly on your MacBook without the burden of paid API costs. You will master performance maximization techniques using Apple Silicon's Metal API and optimal parameter settings for different VRAM capacities, while gaining the ability to build production-level local AI infrastructure based on FastAPI.

Develop various features using Spring WebFlux. This course will teach you WebFlux's essential concepts and practical implementation.

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.

Which AI tool should I learn first? Stop worrying now! - Rated 4.8 by 80 students ⭐️⭐️⭐️⭐️⭐️ - ChatGPT, Claude, Gemini, Genspark, NotebookLM, Gamma, Skywork, Manus, Antigravity, Claude Code, MiriCanvas, Opal, CapCut, and more - Learn the core features of over 15 tools very easily over 20 days. - Through weekly assignments, we provide a course you can "internalize" rather than just "passively listen to." - All-in-one coverage: Prompt Engineering > Image Generation > PPT & Video Creation > Vibe Coding - 4 hours of lecture videos + weekly study materials + assignment certification system

During the Gold Rush, it was said that it was easier to become rich by selling gold mining tools than by mining gold yourself. How about selling programs in the ChatGPT Age of Exploration?

"Work automation... isn't that something only developers do?" "Even if I take an automation course, won't it be difficult without development knowledge?" No, it's not. Even if you aren't a developer and have zero development knowledge, you can apply work automation to your actual tasks. This course was created by me—someone who started as a complete beginner with no coding knowledge—for other complete beginners. Even if you are currently at a level where you've only tried asking questions to AI, you can fully understand and follow along. We will directly build automation cases actually used in the workplace, such as receiving daily automated summary reports of insightful articles and automatically detecting and announcing company anniversaries. Through this process, you will understand the 'methods of work automation' and gradually level up to build your own automation systems. Complete your first automation that can be applied to your work immediately in this course.

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.

The Master Guide to AI for Java Developers! This course shatters the prejudice that AI is the exclusive domain of Python and empowers your Java applications with AI-driven eyes, ears, voice, and even coding capabilities. Grow into an AI Architect based on the OpenAI API. You will directly develop various AI experts such as an AI writer, translator, artist, and coding companion. You will also build a multi-functional AI assistant that integrates core features including text summarization, sentiment analysis, image description, Java code generation, speech-to-text/text-to-speech conversion, and image/subtitle generation. This is a golden opportunity to maximize the competitiveness of existing Java systems by learning how to assign AI roles through system messages and even implement harmful content moderation.

Building an MVP with AI is no longer difficult. However, most projects stop at the next stage. 👉 You’ve built the features 👉 But development doesn't continue Why does this happen? The problem isn't the code; 👉 It's because there is no structure that allows AI to work continuously. --- In this course, based on an existing project, 👉 We will cover the process of building a structure 👉 That allows AI to continue development on its own. --- Instead of simply using AI tools, we will: * Create a docs structure * Define the SSOT (Single Source of Truth) * Execute development on a per-ticket basis * Connect QA and iteration cycles 👉 To complete a single "AI Development System." --- Through this process, you will: 👉 Create a structure where development continues 👉 Even without a human manually coding. In other words, you can: 👉 Build and understand a development system 👉 That operates AI like a team. --- This course is designed for: 👉 Those who want to build a structure applicable to their projects immediately 👉 Those who started development with AI but found it difficult to sustain 👉 Those who want to move to the next level after "Vibe Coding" --- Beyond just learning, we provide an experience where you: 👉 Take action 👉 Build a structure that actually works 👉 And walk away with a framework you can apply to your own projects.

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.

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.

Create a program using the GPT API, and even generate images and videos!

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.