Your AI is no longer in the cloud. It runs directly on your laptop. Learn how to build a completely local Private AI environment using LM Studio and Ollama—for everything from data processing and document analysis to code generation. With no security concerns, no costs, and greater speed— move from simply “using” AI to “putting it to work” yourself.

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.

You know about AI agent frameworks, but understanding how they work and applying them in practice can be difficult, right? Drawing on firsthand experience from Silicon Valley, we’ll guide you from the core principles to practical applications.

You will systematically learn the principles and practical applications of the latest generative AI technologies, from ChatGPT to image and video generation AI and no-code tools. Through seven core topics, including prompt engineering, Copilot utilization, and AI extensions, you can maximize work efficiency and develop creative problem-solving skills.

1. AI practice using an AutoML platform that performs data analysis and AI modeling without coding 2. Carrying out the entire process from data exploration, visualization, and preprocessing for data analysis to AI modeling 3. This course is optimized for passing AICE Basic, an AI certification organized by KT

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

A solopreneur is always short on time. They need to develop automation programs to delegate repetitive tasks to the programs and let people do the creative work.

If you keep getting errors after asking AI to do it, the problem isn’t the AI—it’s that you lack the foundational knowledge to guide it. In this video, we’ll cover the seven foundational concepts that people who get stuck while vibe coding were missing, and explain what each one is and why it’s necessary. 👾 This is explained for people on day zero of coding who have never opened a terminal before.

"We need to do DX/AX." It's always serious in the meeting room, but when you actually get down to the field, don't you feel lost about what to do first and how to do it? You've done a few PoCs, but they never transition to regular operations You bought solutions and equipment, but they're treated as cumbersome tools on-site There's a lot of talk about data and systems, but you can't figure out how to apply them to your current line or process There's no dedicated TFT or team, so you're a practitioner who has to handle both your main job and DX/AX... This course was created specifically for people like you.

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.

We'll teach you the true essence of object-oriented programming. Knowing terms and syntax like class, object, self, super(), and interface doesn't mean you understand object-oriented programming. Object-oriented programming is not simply a collection of syntax, but rather a philosophy on how to solve the problems of increasingly complex software. You can only use it properly when you understand the history and philosophy behind it. In this course, we first explain what problems object-oriented programming was created to solve, and what kind of thinking and design philosophy it embodies, independent of any specific language. Then, using Python as a tool, we gradually cover through hands-on practice how object-oriented concepts are designed and implemented in actual code. Through this course, you'll gain not object-oriented programming that merely follows syntax, but object-oriented programming that you can think through and design, and object-oriented thinking skills that remain solid even when the language changes.

An AI that understands Korean well, handles long documents, and even carries out real-world tasks—that is exactly the direction Solar Open 2 is aiming for. This class provides an accessible explanation of Upstage’s Solar Open 2 technical report in the order of “Introduction → Design → Training → Evaluation.” Technical terms are explained through everyday analogies and visual materials, enabling even beginners to understand “what,” “how,” and “why” as one coherent flow.

With easy explanations and various practical exercises, you can learn web crawling and website automation, and learn various applications such as website creation and ChatGPT usage.

News crawling in the automation lecture... Are you bored? This is a lecture on developing an automation program that will make you an Instagram influencer.

You will learn the meanings of tokens and context, terms you need to know before using AI services, and why LLMs are called “generative” AI. Through a simple hands-on exercise using Claude for Desktop, you will process unstructured text data into structured data and create a PPT and dashboard. You will learn everything from installing Claude Code to its basic usage, building a foundation for starting vibe coding.

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.

Learn how to structure diverse data—including students’ grades, school records, and areas of interest—using the AI-SPARS tool, and leverage an LLM to design everything from major exploration and college/admissions strategies to personalized roadmaps. Rather than simple Q&A, you can immediately apply in practice a systematic AX-style career and college counseling process that progresses from Profile-Interview-Major-College-Admissions Track-Gap-Roadmap-Smart Report-Portfolio.

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.

Master everything from implementing kinematics and dynamics theory with code written entirely from scratch, without open source, to communication interfaces for multi-joint manipulators.

Acquiring probability theory is essential in the study of AI and machine learning. I recommend this to those who wish to study probability theory in more depth.