AI-Powered Video Production Workflow: One-Click Automation System for Non-Majors

It is perfectly fine if you have no prior experience in video editing. This is a practical course where you will learn everything from the basic functions of CapCut to how to analyze and plan short-form advertisements step-by-step. You won't just learn how to add subtitles and cut clips; you will understand the structure of an advertisement and follow along to create videos that actually make people stop scrolling. From Ad Analysis → Planning & Design → CapCut Production. The curriculum is designed so that even beginners can complete a full short-form advertisement just by following along. This lecture is for marketers who are new to video production, and for marketers who now want to create their own content.

Essential concepts every marketer must know - complete guide! Plus insider tips for building experience and skills even outside of companies!

By looking at examples of documents in each field that the instructor has processed, you will practice developing a perspective on viewing documents.

This is a lecture that helps new employees and prospective new hires by organizing essential manners for greetings, emails, phone calls, reporting, messaging, and more within one hour, enabling immediate application in practical work situations.

The ultimate productivity tool, Notion! How to use it properly!

It covers how to build a work automation system using AI and Google Apps Script without complex coding knowledge.

A 2-hour data literacy introductory course for marketers who give up on math and whose minds go blank when they see numbers

A practical beginner course that completes SQL fundamentals in just 3 hours

From SEO Fundamentals Every Real Marketer Should Know to the Latest AI Applications

Even beginners can create decent-looking images with minimal Figma features and design formulas Plus advertising planning methods and hands-on image creation practice

You can establish both the direction of your personal statement and the framework of your portfolio at the same time.

This is a conference for POs/PMs and planners who view products from the customer's perspective and connect them to business.

A class on analyzing customer/sales data with Excel, even without R or Python!

Those who are already good at using Excel can work more effectively, efficiently, and in less time by using Google Spreadsheets.

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.

[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.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

The Gemini agent that works across Google Drive! Put the finishing touches on your Google AI workflow with overwhelming productivity.

"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.

See exam types and trends at a glance! Strengthen your practical skills with approximately 100 questions. The perfect preparation for the AWS AI Practitioner exam, allowing for systematic study even when preparing on your own.

Do you feel stuck every time you have to write a report? Wasting time not knowing what to write, revising over and over because the logic isn't clear, and barely finishing right before the deadline—this is a routine many professionals and students repeat. You may have tried using ChatGPT, but it often stops at simply writing sentences for you. It might produce "plausible writing," but it doesn't create a "result-driven report." This lecture is different. We will show you how to use ChatGPT not just as a task-delegation tool, but as a strategic partner that amplifies your planning capabilities. ✔ How to clearly structure problem definitions ✔ How to apply frameworks to design logical flow ✔ How to strengthen persuasiveness based on data ✔ Strategies to upgrade to performance-oriented reports During the lecture, you will actually complete one of your own work reports, providing a practical experience that leads to immediate results rather than simple theory. Furthermore, by utilizing the latest features like Canvas and file upload analysis, we help you build AI literacy to stay ahead in the rapidly evolving generative AI environment. After taking this course: Your report writing time will decrease, Your logic will become more solid, And your results will become clearer. Experience the moment when report writing is no longer a burden, but a weapon that proves your capabilities.

This course is designed to teach the entire process of 'AI Training Data Construction,' which is essential for successfully executing AI modeling projects. Learners will not simply remain at the theoretical knowledge level, but will experience step-by-step the data construction processes required in actual practice. Specifically, the course covers the entire process from AI training data planning → acquisition → storage → preprocessing → labeling → pseudonymization and transformation through hands-on practice, structured to develop practical skills that can be immediately applied in the field. Additionally, learners will systematically study the most important data management capabilities in AI projects, such as data quality management and security issues, personal information de-identification processing, and dataset optimization. Through this, learners can grow from simple data collectors into data specialists who can proactively plan and execute AI projects. 👉 Through this course, learners will understand how to construct high-quality training data that determines AI model performance and acquire practical capabilities to effectively apply this in real work environments.

[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.

[Strategic Roadmap for System Control and Prevention of Cognitive Atrophy in the AI Era] 1. Introduction: Technical Initiative and Strategic Command (Strategic Command vs. Passive Dependence) A core insight derived from the past 40 years of automotive R&D and corporate management is that entities that lose technical control are highly likely to devolve from beneficiaries of a system into its dependents. In particular, the proliferation of Artificial Intelligence (AI) technology—comparable to high-performance engines—presents a crossroads: it will either leave humans as "passive passengers" of technology or allow them to leap forward as "strategic commanders" who master the system. The indiscriminate dependence on AI observed today is accelerating "Cognitive Offloading," a phenomenon where humans entirely delegate their inherent thinking and analytical mechanisms to machines. This induces the deactivation of the brain's Executive Control Network (ECN) and carries the risk of a structural crisis known as "Cognitive Atrophy," leading to the functional decline of the frontal lobe in the long term. This course aims to present a strategic methodology to strengthen human cognitive capabilities and safeguard intellectual sovereignty in response to this intellectual crisis. 2. Five Core Methodologies for Safeguarding Cognitive Sovereignty ① Maintaining Cognitive Plasticity and Designing Intentional Cognitive Load (Cognitive Gym) The convenience of AI, which provides immediate and seamless answers, can lead to a disconnection in thinking and the omission of critical review processes. To prevent this, it is necessary to design intentional "Cognitive Friction" within work processes. By counter-utilizing AI's automation functions to forcibly delay and deepen the human thinking process, advanced training must be conducted to stimulate neuroplasticity and raise the threshold of thought. ② Establishing an Adversarial Verification System Based on Multi-Agent Systems (MAS) Human cognitive systems are susceptible to "Automation Bias," the tendency to uncritically accept AI outputs. To offset this bias, it is effective to operate a "Critique Agent" or a virtual "Red Team" that analyzes and attacks the vulnerabilities of the logic, separate from the primary model that follows the user's instructions. This forces the process of building defensive logic, thereby activating "System 2 (deliberative thinking)" as defined by Daniel Kahneman. ③ Implementation of Literacy-Based Dual-Track and RQTDW Learning Methods The ability to verify digital tools is directly proportional to one's analog foundational thinking system. While maintaining literacy to deeply grasp the context of text, it is recommended to internalize the 5-step RQTDW roadmap: Read (Deep Reading): Perform a multi-faceted identification of the source of information. Question (Questioning): Pose critical questions regarding logical consistency and the validity of premises. Think (Confronting Contradictions): Analyze and contemplate trade-offs and logical gaps between information. Discuss (In-depth Discussion): Diversify points of contention through virtual or actual discussions. Write (Reconstruction): Refine the results of expanded thinking into human-specific language for systemic internalization. ④ Applying the Sandwich Workflow to Clarify Accountability Delegating the entire work process to AI poses a high risk of cognitive paralysis; therefore, it is essential to establish a rigorous workflow that structurally separates the roles of humans and AI. Context Design Phase (Top Bun): Setting the purpose of the task, imposing constraints, and designing the overall architecture must be performed under human leadership. Data Processing Phase (Meat): Tasks involving repetitive and large-scale resources, such as calculating vast data, sorting, and drafting, are delegated to AI. Final Verification Phase (Bottom Bun): Ethical judgment, precise cross-referencing of facts (Fact-check), and final value attribution are returned to the human domain of responsibility to ensure system stability. ⑤ Hallucination Control and Strengthening Epistemic Boundaries via the SIFT Model AI possesses the attributes of a "stochastic parrot," combining tokens based on probabilistic frequency without a substantive understanding of meaning. Therefore, one must be wary of the "illusion of knowledge" created by AI's fluent output. To this end, a 3-step fact-checking protocol and the SIFT model must be strictly applied in practice. The habit of "Lateral Reading"—tracking original sources and contrasting them with external data—becomes a key mechanism to prevent intellectual free-riding on technical convenience. 3. Conclusion: The Strategic Mission of the Hyper-Intelligent Helmsman While the phenomenon of intelligence is manifested through engineering design, the core agent that controls it in a meaningful direction and creates business value remains rigorous human thinking. This masterclass is designed to ensure that students acquire the capabilities of a "Hyper-Intelligent Helmsman" who controls the powerful power source of AI and designs organizational systems. Strengthen the cognitive muscles of individual members and actively respond to technical challenges. When rigorous engineering control is combined with advanced cognitive abilities, AI will finally function as a strategic asset that drives the sustainable growth of both members and the organization.

This is a 'Practical Linux Troubleshooting Course' where you analyze and solve problems together with generative AI, based on a Docker practice environment that reproduces 5 representative failures that occur in actual Linux operating environments. Even those who were overwhelmed about where to start examining problems can learn the problem-solving approach and thought process of field engineers through AI guidance.

Beyond the era of simply using AI, we are now in an era that requires people who can design AI. This course is a master roadmap that systematically organizes the entire design map of AI agents, from "Introduction → Structure → Design → Operation." Based on RAG, Tool Calling, Memory, and Multi-Agent structures, you will learn how to design and scale AI agents from an architect's perspective. If you want to grow into someone who designs AI systems rather than just someone who "uses" AI, this course will provide the direction.

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Many aspiring entrepreneurs have the 'What (Idea)' but fail because they don't know 'How (Plan)' to refine it. Don't give up just because you lack writing skills or can't find market data. Through Startup Build-up, verified by successful government grant recipients, we will translate your ideas into the winning language of business.

We will teach you about AI, especially Generative AI like ChatGPT, by learning about it from various angles and showing you how to use AI tools that can be applied in practice. It consists of content such as marketing planning utilizing Generative AI, and an introduction to and utilization of Generative AI tools helpful for marketing content development (ChatGPT, image Generative AI).

"The Fourth Industrial Revolution, AI factories... The terms are familiar, but can't you visualize the structure?" Smart Factory, often called the future of manufacturing. While related articles pour out and it appears as a required competency in job postings, the barrier feels far too high for non-majors. "Did you give up because of abbreviations that sound like alien languages, such as PLC, MES, or ERP?" "Are you afraid to even start because you lack knowledge in coding or engineering?" Don't worry. This lecture deals with 'structure,' not 'engineering.' Instead of complex text, we will help you complete a full map of the smart factory in your head using intuitive drawings and diagrams, just like assembling Lego blocks.

This lecture teaches how to generate images using DALL-E3 (DALL-E). Through basic functions, a 3-step prompt strategy, and hands-on image generation practice, participants can become creative image creators.

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

This is a course on creating blog images using DALL-E 3. This course provides practical knowledge and hands-on opportunities from the basics of image generation technology to advanced usage techniques and problem-solving strategies.

The real story of an AI-native company run by GolbinHacker, the 1st place winner of Kakao AI TOP 100 and author of the bestseller "The Best Prompt Engineering Lecture." It explores how just two developers build and operate a service, along with the new competencies developers and organizations need in the AI era through real-world cases.