UI/UX portfolio using AI

1. What is the real 'problem' you are facing? Those who have worked as engineers, researchers, or business writers and have attempted to introduce AI into their workflow usually hit the following fatal walls: The Paradox of 'Volume vs. Value': When you ask a question, plausible-sounding text pours out, but when you try to apply it to actual work, it is useless because the facts are wrong or it lacks depth. The uncontrolled mass production of content ultimately only results in costs such as data bleeding and hallucinations. The Limits of Casual Chatting: The quality of the output depends on 'luck' every time. An AI that was smart yesterday gives nonsensical answers today, and when you force a specific template format, a 'degradation of intelligence' occurs where the model's reasoning ability plummets. Isolation of Knowledge: There is no standardized methodology to convert the experienced 'tacit knowledge' accumulated in the field over decades into 'explicit knowledge assets' that all organization members can copy, paste, and use. Ultimately, many people have downgraded AI to a mere "assistant for light summaries or email drafts," while still suffering through manual labor for critical business tasks such as high-density engineering or strategic planning. 2. How to solve these problems with 40 years of R&D tacit knowledge and systems engineering Throughout my life, I have successfully led projects worth hundreds of billions of won by passing through the rigorous process gates of ultra-precision internal combustion engines and Systems Engineering (MBSE). I have transplanted this engineering intuition directly into prompt design, embedding a paradigm into this course that treats prompts not as simple questions, but as 'system configuration files (Config Files)' that control statistical uncertainty. Through this course, students will acquire the following specific solutions: Introduction of XML-based Structured Architecture: We exclude ambiguous prose prompts and design guardrails to prevent information bleeding and prompt decay through precise XML tags and Markdown fences such as <role>, <task>, <constraints>, and <context>. 7-Step Gate Process Chaining: By borrowing the step-by-step control processes of automotive R&D, you will be able to perfectly command a 7-step chaining workflow—from instruction standby to literature review, critique and self-verification, and final compilation—where the AI verifies its own logic as it progresses. Hybrid Decoupled Pipeline Control: When utilizing the latest reasoning models like o1 or DeepSeek-R1, you will secure the control to preserve 100% of intelligence by handling skeleton code for a 'Reasoning-Formatting Hybrid Decoupled Pipeline' that bypasses the phenomenon of intelligence degradation caused by format constraints. Quantitative ROI Quantification of Business Value: You will master ROI formulas and KPI models to prove validity to C-level executives with figures. For example, when this pipeline is actually built in-house, the average lead time for writing technical white papers or regulatory compliance documents is reduced from 4–6 months to within 10 days (a 93.3% reduction), and more than 65% of research costs are saved as marginal costs.

Introducing AI utilization methods perfectly tailored for office workers and civil servants, delivered directly by an instructor who has satisfied over 10,000 students through hundreds of invited lectures.

This course is for those who have ideas but don’t know development or design and feel overwhelmed about where to begin. I wasn’t good at development from the start either. By repeatedly using AI for real work and personal projects, I’ve built things one by one—from “I’ll Take Care of It,” a service that solves everyday problems, and ENGIN, an English-learning app, to AI mini-games and a video production automation system. In this course, I won’t just show you the finished results. Through real screens and production records, I’ll show you how to break an idea down into a size AI can understand, how to decide on the first feature, how to request tasks from AI, and how to personally check and revise what has been created. You don’t need to understand all the code before getting started. You can begin by summarizing the problem you want to solve in one sentence and entrusting AI with one small result. Turn the ideas that have existed only in your head into a visible screen and a working first version you can experience for yourself.

This is a practical Claude application course for AI beginners and non-developers. You will directly create results that can be immediately applied to real-world tasks, such as PPTs, content, YouTube videos, and product detail pages using Claude. Learn how to maximize work productivity using AI without any coding.

"Are you tired of repetitive daily tasks and expensive AI tool subscription fees?" This course teaches you how to create an 'Automation AI Agent' that will completely transform your work through intuitive 'Node' connections, even if you know nothing about coding. To solve the 'high cost' issue of existing tools like OpenClo, you will learn smart automation design methods where the computer quickly handles simple calculations and calls the AI only when absolutely necessary. From YouTube notifications and receipt bookkeeping to RAG document searching and automated email replies, build your own 24-hour customized AI assistant at almost zero cost through 9 practical examples!

This course consists of a curriculum designed to achieve overwhelming efficiency in various fields such as planning, development, marketing, and job preparation by utilizing 'Perplexity AI,' an AI answer engine that goes beyond the limitations of traditional search engines.

Even if you are not a major or a designer, you will learn how to directly create and modify web UIs, proposals, and design systems using Claude Design and Figma. To ensure immediate application in practice, the course proceeds step-by-step with a focus on hands-on practice—covering everything from the differences between Claude Code and Claude Design to installation, plugin utilization, component-based UI production, design modification, and methods for applying them to live services. This lecture is designed to help developers, planners, and marketers who found design tools difficult to experience rapid result-making through AI and component-based workflows.

Is your skill stagnating because you keep asking AI to 'just whip something up'? This course dissects the principles and philosophy of the 'Cocrates Harness,' a rigorous constraint system that fundamentally blocks the sloppy generation of LLMs. Defy the gravity of AI convenience and discover the cheat code to rapidly growing into a 'true top-tier architect' who commands and controls every design context!

The goal is to cultivate a full-stack perspective that allows individuals to lead the entire product lifecycle, covering everything from research automation and backend data integration to the deployment of live dynamic websites. We empower those who want to strengthen their competitiveness in the AI era by providing the ability to use these tools as a powerful engine to turn ideas into reality.

AI literacy refers to the "ability for general users, not just technicians, to effectively utilize AI in their practical work and daily lives," as well as the "competency to critically evaluate AI." This is a practice-oriented literacy course designed for non-experts to understand the core knowledge for "utilizing" AI well—covering everything from prompt engineering to security understanding, expansion, automation, and the structure of language models.

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.

This is a practical course that uses Codex to connect business planning, website creation, marketing materials, task organization, and email automation. Even if you are not a developer, you will learn how to delegate tasks to AI and refine the results using Notion, Linear, Figma, and Google Workspace in an actual workflow sequence.

From meeting preparation to writing minutes, AI does it all! The first in our series on using AI Agents for company work!

This is a practical guide to AI-based career exploration for children in grades 4–6. Using the AI-SPARS algorithm, it precisely analyzes a child's interests, aptitudes, and values, teaching how to complete a customized career and academic portfolio prepared systematically from elementary school. Parents and teachers can directly implement a data-driven career design process that suggests a direction rather than a single fixed answer.

We invite you to become a ‘Top-Tier Enterprise AI Systems Architect’ Do not remain a micro-level technician (Prompt Writer) who merely assembles libraries created by others or polishes prompt sentences. From mathematical first principles to runtime control-loop kernels and autonomous recovery infrastructure — through 40 years of practical engineering insight that has driven industrial operations in South Korea, I will firmly guide you to become a top-level ‘Enterprise AI Systems Architect’ who protects your company’s business and digital sovereignty. Now, begin the great journey of transforming uncontrollable AI into a perfect industrial core. “Why does an AI that ran perfectly in a demo start spouting strange nonsense or bring the pipeline to a halt as soon as it is deployed to production?” “Why do AI projects that so many companies launch with great enthusiasm ultimately fail to escape the ‘PoC (Proof of Concept) swamp’ and get abandoned?” These are the most desperate questions that countless developers and systems architects I have met in the field have asked me. Hello. I am Hongjip Kim, who spent more than 40 years in the powertrain R&D division of the South Korean automotive industry (including 17 years as an executive in Hyundai Motor Group R&D), led the export of engine and drivetrain technologies worth 130 billion won, and commanded operations as the CEO/CTO of a listed mid-sized manufacturing company. From the perspective of an engineer who has spent decades in mechanical engineering and precision-control environments, a ‘risk of fatal uncertainty’ lurks behind today’s frenzy to adopt generative AI. In mission-critical industrial environments where even a mere 0.1% error or mistake can directly result in the destruction of physical equipment worth hundreds of millions of won and an enterprise-wide shutdown, integrating a probabilistic chatbot that simply relies on probability to generate plausible text directly into a service is like carrying a ticking time bomb into a fire. This course was designed to impart the “practical engineering methodology for training uncontrollable probabilistic AI into the most robust industrial control core, one that allows not even 0.000% of syntax errors.” 1. The 3 Major Fatal Bottlenecks You Face in the Field (Problem) Many engineers attempt to challenge production environments using an approach limited to one-off prompt tuning (Vibe Prompting), only to become frustrated when they encounter the following 3 structural defects: Finite Context and ‘Lost in the Middle’: As conversations or multistep executions grow longer, critical system instructions are pushed aside and the context window is exhausted, causing the system to lose its memory and amplifying hallucinations. Nondeterministic Outputs and Cascading Pipeline Collapse: Tiny probabilistic fluctuations, such as one missing closing bracket in JSON or an incorrect type, can paralyze legacy ERP/CRM API calls and destroy data integrity. Untrusted Code Execution and Infrastructure Security Bankruptcy: When scripts autonomously generated by an agent run in a non-isolated host OS environment, they create risks such as kernel escapes and sensitive-data leakage. As such, AI malfunctions in industrial environments are not merely quantitative accuracy problems; they become a massive financial disaster in the form of asymmetric business loss (Asymmetric Business Loss). 2. ‘How’ to Solve These Problems Perfectly (Solution) This course differs fundamentally from commercial courses that teach only how to use fragmented off-the-shelf tools. By combining 40 years of hands-on field expertise with computer systems engineering, it delivers 3 hardcore architectures for vertically integrated, system-level control of probabilistic AI: ① Move Beyond Prompting to ‘LLM-OS & Context Orchestration’ Following Andrej Karpathy’s paradigm, redefine the LLM not as a conversational respondent but as the central computational core (CPU) of a computer. Systematically organize the context window as ultra-low-latency volatile RAM, the internal vector DB as Disk, and external APIs as an I/O bus. Through MemGPT hierarchical virtual-memory paging, preserve critical state without saturation even during infinite conversations, while scaling a dynamic agent network through MCP-based Liquid Swarm MAS, minimizing token costs. ② ‘Deterministic Harness Engineering’ That Constrains Probabilistic Hallucinations to 0.000% Leave the language model’s creative flexibility open only during the Reasoning phase, while firmly confining the physical output layer that interacts with external systems using mathematical Boolean algebra and compilers. Apply EBNF / XGrammar-based CUDA logit masking to forcibly block the generation probability of invalid tokens at P = 0.000%. Form a physical security isolation ring so that code generated by agents runs only once inside a Firecracker MicroVM micro-virtualization sandbox with 5ms snapshot restoration capability. ③ ‘High-Reliability MLOps·LLMOps Autonomous Recovery Infrastructure’ Without Wasting GPU Resources Build vLLM PagedAttention and S-LoRA hot-swapping to suppress idle VRAM waste to below 4%. When a multi-agent API fails, restore data consistency 100% through SagaLLM reverse compensation transactions. Through an OpenTelemetry/Langfuse distributed observability network, defend system availability by executing an unmanned automatic canary rollback whenever a decline in the RAGAS faithfulness score (Data Drift) is detected. 3. Practical Value That Drives Spiral Growth (Pedagogy & ROI) This course is systematically designed according to the 5 levels of Bloom's Taxonomy. Starting from simple theoretical recall (Remember), learners directly code and validate a 5-stage debugging pipeline (analyzing deceptive baseline trap source code ➔ deconstructing adversarial engineering ➔ establishing a Robust integrity pipeline ➔ calculating the TEI ROI formula ➔ SOTIF/ISO 42001 governance). Going beyond the intuitive satisfaction of simply “working well,” I will apply the Forrester TEI (Total Economic Impact) financial model to visualize, from an executive perspective, how much the AI system you build reduces your company’s rework cost (Rework Cost), avoids failure risks worth hundreds of millions of won, and proves an ROI of more than 200%.

Using AI has become easier, but model cards and papers are still difficult to read, even just a few lines. Although you can look up the meanings of individual words, it’s not clear how those words connect to one another. This course builds up around 160 essential terms that frequently appear in AI documents, in the easiest order to understand them, so that in each lesson you can accurately read a single sentence from an actual document.

Have you introduced AI but still find yourself losing time to repetitive tasks? The problem isn't the AI; it's the 'system.' This course guides you through the process of building a team of six AI assistants—including an executive assistant, content assistant, marketing assistant, CRM assistant, and personal productivity assistant—all using Notion AI. Based on my experience automating hundreds of repetitive tasks in real-world business settings, we will build actual workflows from start to finish, covering everything from organizing notes and automatically generating meeting minutes to blog writing, CRM construction, and automated KakaoTalk notifications. After completing this course, you will have a system where your own AI assistant team works automatically, powered solely by a Notion Business plan.

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.

Why not streamline your narration recording with AI? *This course includes the use of AI.* "Are you spending your precious evening hours recording narration for presentation materials?" "Do you want to maintain high quality for your side-hustle video content, but lack the time and space to record?" What if you could delegate that time-consuming "voice recording" task to an AI voice that sounds exactly like you—your "voice double"? This is a highly practical introductory course designed for busy business professionals to master the AI voice generation tool "ElevenLabs." You will learn how to fundamentally transform your production process by ultimately creating your own "voice double." "Streamline" tedious recording tasks and reclaim your most valuable asset: "time." We will systematically provide specific workflows and techniques from an expert's perspective to achieve this. **In this course, you will acquire the following skills:** * Techniques to master ElevenLabs and generate high-quality Japanese audio. * The specific workflow to have AI create your own "voice double" (voice clone). * Voice recording methods taught by a vocal coach to extract maximum performance from the AI. * Strategies for utilizing your created AI voice for both your main career (presentations, training materials) and your side hustle (YouTube, SNS). * Essential risk management knowledge regarding copyright and law to avoid failures in commercial use. **Unique features of this course:** This course is more than just a manual on how to use a tool. As a vocal coach, the instructor will generously share expert insights—from how to read and project your voice for the submission samples to recording methods that enhance quality—to ensure you get the best performance out of the AI. Furthermore, ElevenLabs offers plans that even AI beginners can use with confidence. You will be amazed by the quality of the AI voice you can test starting with the free plan. Rest assured, we will guide you step-by-step: from learning basic knowledge and safe usage to upgrading to a paid plan to create your own "voice double." **▼ This course is especially recommended for:** * Business professionals who want to dramatically improve productivity in document creation. * Those who want to leverage their professional expertise to share high-quality information through a side hustle. * Creators who have given up on audio content due to time or location constraints. * Those who want to acquire the latest AI technology as a concrete skill for business improvement. * Those who want to leave repetitive tasks to AI and focus on core activities like planning and strategy. **▼ Requirements for taking the course:** * Basic PC operation skills. * An internet connection. * An ElevenLabs account (The free plan is sufficient for the beginning of the course. A paid plan is recommended for the practical voice cloning section). **Enroll now and transform the way you work!** The skills gained in this course will become a powerful weapon that you can use for a long time in both your main career and your side business. Free yourself from tedious recording work and take a new step toward accelerating your business!

The lecture explains why the harness is more important than the model through the lens of Claude Code architecture. It also covers how to design a Claude Code work system around six structures: Context Harness, Permission Harness, Verification Harness, Tool Harness, Subagent & Worktree Harness, and Debugging Harness. It then connects these concepts to CLAUDE.md, session management, controlling large codebases, parallel worktree operations, error log analysis, and tracking environment variable and configuration scope issues, helping you establish practical standards for continuing to use Claude Code in real-world backend and DevOps work.