Local LLM Utilization Guide Part 1 - Using small LLM(sLLM) & Evaluating and Improving LLM Performance

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

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.

A course to learn website crawling methods using ChatGPT. Get a preview of the transformed future ChatGPT will create.

This is a lecture where you can learn how to use Git & GitHub step by step from the basics to advanced content through various practical exercises. Understand the principles through intuitive examples and learn how to use Git & GitHub through practice.

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

Through AI company reviews, we examine how AI technology will change our present and future through various cases. By examining the necessary elements for carrying out AI projects, we prepare for the upcoming AI Transformation.

From the basics of deep learning natural language processing to the latest models such as Transformer and BERT, learn the principles and utilization methods of deep learning natural language processing (NLP) through various examples and practical code implementations.

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

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

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

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

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.

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 course covers data analysis using ChatGPT and Pandas utilization. Get a preview of the changed future ChatGPT will create.

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.

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.

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.

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

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

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

We will examine methods for collecting and analyzing user requirements to plan LLM services.

Learn AI utilization methods and performance improvement strategies tailored to real-world business situations. (i.e., you won't learn things like automatic short-form video generation.) This is a practical course where you learn to leverage AI not merely as a tool, but as an ultimate instrument for business efficiency. By utilizing various generative AI and the latest AI agents such as ChatGPT, Gemini, NotebookLM, Gesnpark, Skywork, etc., you will master AI prompt utilization → AI data analysis → and AI task automation implementation, all at once. This class is optimized for planners, marketers, managers, founders, and others who wish to acquire business productivity and performance enhancement strategies directly applicable to their work.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

[Up-to-Date Knowledge for Current Times] 1. Changes brought by AX, ChatGPT, and robot technology. 2. Commonalities of Blockbuster-Kodak Film-Nokia. 3. Five Current AX Keywords. - OOOO coin to maintain dollar hegemony. - Musk's OOOO to cut government operating costs. - Trump's OOOO strategic reserve. - China's OO kindergarten, OO receiving private education. - China's OO factory, with no workers, OO is no longer needed. 4. ChatGPT/Gemini/Grok - Write prompts based on previously learned content and compare results - Generate images with Claymotion infographics

AI that finds everything for me! A practical solution for AI research, unifying planning, research, analysis, and communication

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

This course is a hands-on masterclass that completely dissects the core technological evolution of generative AI, from LDM (Latent Diffusion Model) to DiT (Diffusion Transformer). We directly analyze the latent space-based learning principles of LDM, the structure of Stable Diffusion, and the implementation methods of the latest Diffusion Transformer through papers and code. Students will systematically learn the latest trends and structural evolution of generative models by directly implementing LDM, CFG (Classifier-Free Guidance), and DiT models using PyTorch.

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.

How to Build an Efficient Startup Workflow System with Just Notion 🧑🏻‍💻 (Practical Workflow Templates Provided by Practitioners)

Digital transformation (DX) is not a choice but a necessity. This course serves as the first step in digital transformation for all employees, providing easy and clear explanations from core DX concepts to business innovation cases. Don't fall behind in this changing era—develop the power to grow yourself and lead organizational innovation! Please don't overthink this lecture and take it with a light heart.

This course is a specialized program that covers practical application strategies for utilizing artificial intelligence (AI) in the construction and civil engineering fields. In the construction industry where digital transformation is accelerating, AI is driving innovation across design, construction, safety, and quality management. This course focuses on learning practical application cases that can be utilized in actual field sites, including smart construction, digital twins, AI-based equipment control, safety monitoring, and quality verification.

We implement the latest Transformer-based PixArt and lightweight adaptation SANA step by step from theory to code. Building on DDPM·DDIM·LDM·DiT covered in Parts I·II, we complete hands-on practice including text encoder integration, samplers (DDIM/ODE), v-prediction/CFG tuning, and small-scale data style fine-tuning.

[McKinsey Alumni Kim Jaesung's Problem-Solving Q&A: We'll Solve Your Problems Together] Required! Prerequisite Course: McKinsey Alumni Kim Jaesung's AI-Powered Problem-Solving & Research Special Lecture https://inf.run/LmvrD 'Theory-only lectures, step aside!' A magical solution video that solves real practical problems together on the spot! This is a video series where Kim Jaesung, a McKinsey alumnus and AI expert, meets with each person individually in a 1:1 Q&A format to structure and solve your problems. From career paths and minor concerns to massive topics like AI that's shaking the world and improvement directions for industries as a whole! Each video will be uploaded for individual purchase. Paid course students will have the opportunity to actually participate through a quarterly lottery drawing! (The more of Kim Jaesung's courses you take, the higher your chances of winning!) [Concept] This is a 1:1 immediate Q&A format meeting with individuals, with the concept of industry experts and strategy experts coming together to approach the right answer. Participants have been extremely satisfied. (You can see and hear this in their testimonials!) The key to this video series is that strategy expert Kim Jaesung doesn't receive the topic in advance, but through strategic questioning and answering, we get closer to the right answer together. Experience the magical solution that naturally elicits the reaction "This actually works?!" lol, based on strategy and structuring rather than relying on intuition and experience! The free version (~10 minutes) will be available to everyone, and the full version will be available to Inflearn course students or YouTube channel [Kim Jaesung's Problem Solving] 'Premium Membership' subscribers. If you wish to participate, please send an email to jaesung_kim@jcurvepartners.ai with the subject line [Coffee Chat Application] In the email, please include your name, age, contact information (mobile phone number), occupation and years of experience (students are welcome), detailed reasons for applying, and attach a screenshot of your enrollment in Kim Jaesung's Inflearn courses. Selected applicants will be contacted. (Personal information of non-selected applicants will be immediately discarded after 3 months) When appearing in the video, using a pseudonym or not revealing your company name is possible, but if you wish for face blurring, voice modulation, or other modifications, participation is not possible. By consenting to video recording, you are deemed to have agreed that the video may be reprocessed and used on Inflearn and Kim Jaesung's YouTube channel.

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.

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).

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.