From Basics to Practice! Complete Mobile UX/UI Design

A must-have course for designers, service planners, and PMs who want to do their jobs better! We will teach you what you need to know for each digital product, industry, and user journey based on real-life cases.

If you know how to use Figma but are not familiar with using components, I think this tutorial will be helpful.

"In such a busy world, you can create a portfolio quickly using AI?" From problem definition to research synthesis, ideation, and prototyping! Use AI as your practical partner to quickly build a high-quality UX/UI portfolio. You can strategically utilize not only the latest AI tools but also proven tools consistently used in the industry to fit your project.

One working prototype is better than 100 pretty screens! Create prototypes that function like the real thing using conditional logic in Figma, and cultivate design thinking skills that remain steadfast even in the AI era.

This explains intermediate-level After Effects techniques and above that can be utilized in practical work. Although explained using CC2023, it focuses on fundamental principles regardless of version. Rather than wasting time on tool explanations, I've prepared material that enables proactive research.

We have compiled our know-how from more project experience than anyone else to create a lecture that provides an understanding of the surefire screen implementation method and an easy and quick method.

There are app/web ideas that they want to implement, but they are at a loss as to where to start due to their lack of experience in app service planning, startup representatives who want to learn planning systematically in a short period of time, and junior planners who want to learn the planning work process and know-how of experienced planners. We will teach you a new planning method using Figma and the work skills of a PM with 17 years of experience from the basics so that you can become an expert.

You can enhance your mobile web production skills, which are the most competitive assets for publisher employment and practical publishing work. You will be able to solidify almost all production methods and know-how required to create mobile webs as a publisher. In particular, to cover much of the design ability required of publishers and developers these days, we have provided detailed explanations of the process of working on mobile web UI design using Figma. A key strength of this mobile web publishing course is the detailed instruction on how to create HTML wireframes for every single page. Through this lecture, your ability to create HTML wireframes will improve significantly. In mobile web publishing, you will acquire practical skills comparable to real-world work by learning how to perfectly adjust layouts for mobile and tablet devices using CSS variables (Var). You will fully develop intermediate-to-advanced practical CSS skills, centered around Flex layouts.

Full-stack course from Figma design to AI-powered coding and deployment!! [Figma + Vibe Coding (HTML/CSS/Tailwind/React) + Git + Vercel Deployment] Your design exactly as it is!! Complete it with Vibe Coding without a single pixel of error! A full-stack guide to increasing practical productivity by 5x using AI! You too can become a full-stack designer capable of both design and coding. ✅ Implement your design intent without a single pixel of error ✅ Design architecture that AI understands ✅ Prompt engineering skills to precisely control AI ✅ Ability to skillfully fix code generated by AI Experience the amazing reduction of time from design to coding and deployment by 1/5.

Do you have a foundation in HTML, CSS, and JavaScript (jQuery)? But are you unsure how to create an entire website? If so, try implementing a shopping mall's main page by referencing a design. We'll share know-how on implementing a website by referencing a completed design and understanding the planning intentions and detailed aspects of the design.

This course provides UX principles and practical know-how necessary for planning and designing AI products. We will explore user-value-centered AI utilization methods, UX planning and design methods using AI, core UX principles and theories learned through everyday design cases, and UX research and data analysis methods for providing a better experience.

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.

Midjourney, the premier tool for image-generating AI! From basic usage to real-world application through practical design projects, all in one go!

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.

I have worked at seven different small startups that had neither data analysts nor user researchers, and I've stumbled through various trials and errors. I will share the many realistic challenges a UX designer can face, along with the deep insights I gained while navigating through those difficulties.

Seo Ja-young, Kiki, and Kang Young-hwa talk about self-growth methods and soft skills based on cases they experienced in their careers.

[Process Optimization Roadmap: Eliminating Unnecessary Capital Investment and Converting 'Hidden Factory' Opportunity Costs into Tangible Profits] 1. Introduction: Transition to Intelligent Processes and the Prerequisite of Standard Operating Procedures For modern enterprises to maximize business value by adopting Artificial Intelligence (AI) technology, the rigorous standardization of physical processes and work procedures on the shop floor must come first. An intelligent system built upon an unstructured data environment lacking standardization will struggle to achieve optimal performance; instead, it is highly likely to amplify process uncertainty and act as a risk to the entire system. This training course aims to present a strategic methodology for discovering latent profit sources within the so-called 'Hidden Factory' and converting them into an engineering foundation that AI can autonomously control and optimize. 2. [Analysis] Quantitative Data-Based Field Diagnosis and Analysis of 'Baseline Losses in Critical Indicators' Many manufacturing sites tend to overlook potential operational losses by settling for superficial performance indicators. When Overall Equipment Effectiveness (OEE) is precisely analyzed through engineering decomposition techniques, the following structural losses are identified: Availability 90%: While external uptime is secured, power loss due to minor stoppages occurs continuously. Performance 90%: A slowdown in actual speed compared to theoretical cycle time has become chronic, yet there is no reference point to recognize and improve this. Quality 90%: A defect rate reaching 10% is evaluated as a critical figure that undermines the reliability of the entire process. The actual OEE, calculated by the multiplier effect of these three indicators, is only 72.9%, meaning the remaining 27.1% of opportunity cost is buried within the 'Hidden Factory'—unidentified by data. Therefore, the primary task of AI adoption is to quantify the source of this waste and ensure process transparency. 3. [Critique] Redefining Strategic Priorities: The Conflict Between Operational Excellence (OPEX) and Capital Expenditure (CAPEX) Prioritizing the expansion of new facilities (CAPEX) as a solution to declining productivity can be a strategically dangerous decision. Adding lines to a low-efficiency structure where OEE remains at the 60–70% level results in replicating fundamental inefficiencies, leading to an exponential increase in management costs. Before large-scale capital injection, maximizing Operational Excellence (OPEX) to break through the physical limits of existing assets must take precedence. Only when standard operating procedures capable of achieving the world-class standard of 85% OEE are established can a virtuous cycle be built—one that dramatically improves production capacity through integration with AI without additional investment. 4. [Evaluation] Integration of Data Architecture: Establishing an ISA-95 Based Decision-Making System The disconnection between the financial indicators of Enterprise Resource Planning (ERP) and the operational data of the Manufacturing Execution System (MES) is a core cause of information distortion and delayed decision-making. To resolve this, the international standard ISA-95 architecture is applied to organically integrate management strategy with the physical production site. Establishment of a Single Source of Truth: Complete a data pipeline where all dynamic field data is synchronized in real-time with the enterprise management system. Conversion of Indicators into Financial Value: By intuitively linking the impact of minor field stoppages to actual operating profit and cash flow on financial statements, an objective, data-driven performance evaluation and decision-making system is established. 5. [Execution] 4-Step Strategic Roadmap for Intelligent Process Management Implement an advanced strategy that fuses AI technology with human engineering insight based on strictly standardized procedures. Predictive Maintenance and Utilization of P-F Intervals: Build a predictive maintenance system by monitoring the P-F Interval—the period from a potential failure (a precursor to equipment breakdown) to a functional failure—in real-time. Digital Twin-Based Simulation and Minimization of Trial and Error: Practice a 'Zero-Trial' strategy that prevents physical losses by verifying various scenarios within a virtual environment before implementing process changes. Quantitative Control of the 6 Big Losses: Continuously track and manage the six core waste factors that hinder profitability—equipment failure, setup/adjustments, idling/minor stops, reduced speed, process defects, and reduced yield/rework—through AI. Digital Advancement of Total Productive Maintenance (TPM): Enhance the reliability of Human-in-the-Loop systems by establishing a proactive culture where field operators voluntarily detect and respond to signs of equipment abnormality. 6. Conclusion: Securing Technological Leadership Through Standardized System Architecture Technical knowledge can be transferred through education, but the insight to dominate process flow only manifests upon a sophisticatedly designed standard system. This masterclass aims to provide a precise engineering blueprint for transforming your production site into an intelligent asset. Establishing standardized work procedures and ensuring data integrity are essential prerequisites for the AI era. Only on a firm systemic foundation will AI function as a true intelligent production site that drives corporate growth.