GPU Principles and CS Knowledge You Need to Know in the Era of AI Coding

This is our 'actual real-world workflow,' and we are releasing the 'onboarding video' used for planners and developers joining our company. It teaches you how to design service screens without a designer and create UX flows and prototypes even if you don't know Figma. Our company maximizes productivity by prototyping quickly during service planning to enable fast decision-making, finalize necessary features, and utilize them directly in front-end development. If the response is positive, I will upload more lectures on other "real-world workflows."

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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.

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

■ Course Overview Are you facing any of these challenges? - Spending too much time creating presentation materials, leaving no time for other tasks. - Feeling uncomfortable with design work in PowerPoint or Canva. - Wanting to create easy-to-understand slides but lacking confidence in structure and visual presentation. - Interested in AI tools (e.g., Gamma or felo) but unsure which one to use or how to use it. - Wanting to create high-quality presentation materials that convince clients or supervisors in a short amount of time. This course is for you. In this course, you will learn how to use the AI presentation tool "irusiru" to create high-quality, easy-to-understand slide decks in a short time. We will compare it with tools like Gamma and felo, highlighting irusiru's unique strengths and the specific scenarios where it excels. Reduce the time spent worrying about design and simultaneously improve your work efficiency and persuasive power. The main contents of the course are as follows: - What is irusiru? Basic functions and differences from other tools. - How to design the optimal slide structure based on your objective. - Steps and practical tips for creating materials using AI. - Practical Session: How to create presentation materials using irusiru. ■ What You Will Achieve By taking this course, you will: - Significantly reduce creation time by utilizing AI-powered automatic slide generation. - Be able to create high-quality slide materials in a short time using irusiru. - Understand the differences between irusiru and other tools like Gamma or felo, and be able to choose the best tool for your purpose. - Reduce the burden of creating presentation materials and improve overall productivity. ■ Who This Course Is For - Business professionals struggling with the excessive time it takes to create presentation materials. - Non-designers who are not comfortable with design work. - Business professionals looking to streamline daily tasks using AI tools. - Side-hustlers and freelancers wanting to improve the efficiency of creating client materials. ■ Requirements - Basic computer skills and internet literacy. - Ability to use a web browser and perform Google account logins. - While experience creating courses on Udemy will help with understanding, beginners are more than welcome. I look forward to seeing you in the course! Hiroshi Wada

We provide an easy understanding of the concepts and principles of generative AI from a humanities perspective, including literature, film, music, and history, while exploring the cultural impacts and life changes AI will bring. We offer practical insights and strategies on how individuals and companies should respond and prepare for the AI era.

With the advancement of generative AI, many companies are pursuing AX (AI Transformation). However, in the actual field, there are not many educational programs that systematically teach what to do and how to do it compared to the demand that "AX must be done." While most AI education focuses on how to use generative AI or write prompts, this course focuses on the "AX Strategy Planning Methodology" for transforming corporate tasks and services into AI-based ones. This course is based on the practical experience of a 25-year expert who has performed DX/AX consulting and training for large corporations, the financial sector, public institutions, and various companies in the actual IT field. It allows you to learn from a practical perspective not just how to use AI well, but which tasks should undergo AX, to what extent AI should make decisions, how to control risks, and how to design and verify AX projects. Furthermore, it systematically covers core content necessary for actual AX implementation, from understanding the essence of AX to AI thinking systems, AX design methodology, Human-AI role separation, Guardrail design, and KPI and verification structures. In particular, it goes beyond simple theoretical education. Based on real corporate cases such as insurance underwriting, customer consultation, manufacturing quality, internal work support, marketing recommendations, development productivity, and management decision-making, it provides guide templates and sample materials for AX problem definitions, AX hypothesis definitions, AX performance designs, AX service structure diagrams, Guardrail designs, and AX verification plans. This ensures that after taking the course, you can secure the practical capabilities to easily plan and promote actual AX tasks. The biggest differentiator of this lecture is that it teaches how to plan and design AX from the perspective of someone who actually performs AX projects. Specifically, by providing AX strategy planning output templates and seven industry-specific AX cases that can be used in the field, it is designed so that students can refer to cases most similar to their own work and apply them immediately by modifying them to fit their environment. In short, this is not a course to create AI users, but a process to create AX strategy planners who can design and execute a company's AX.

The 0s and 1s we talk about, HIGH and LOW, logic gates and flip-flops— they all emerge from the physical event of analog signals crossing a threshold. If so, wouldn't understanding the world before logic— the movements created by current and voltage— be the true beginning of circuit design? This course takes that first step together.

No more outdated PPTs even after working all night! A veteran instructor with 25 years of experience has packed in only the essential core skills needed for practical work, from PowerPoint basics to the latest AI utilization methods. Even without design sense, we'll teach you 'everything about presentations' that cuts your work time in half and doubles your quality.

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will gain a broad range of knowledge, from establishing AI-based system testing strategies to designing and executing test cases, as well as utilizing AI for test support. This course is based on the ISTQB AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

No Coding Skills Required: Build Your Very First Service with Google Stitch An All-in-One AI Development Workflow That Seamlessly Connects Every Step from Planning to Deployment

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

Learn the core principles and practical implementation of Classic RAG, Graph RAG, and Agentic RAG. Design a dynamic routing system that optimizes token efficiency and latency, and build a long-term memory system that combines GraphRAG’s relational network reasoning with Agentic RAG’s self-evaluation loop. This course develops advanced RAG architecture design skills that can be applied directly in real-world settings.

The semiconductor industry is a representative manufacturing sector where production facilities, control systems, partners, and data are closely interconnected. For this reason, even a small security incident or system failure can lead to production shutdowns, quality issues, delivery delays, and technology leaks. This lecture explains the OT security threats that can occur at semiconductor manufacturing sites in a way that even beginners can easily understand. Rather than focusing on complex technical explanations, it centers on what security problems can arise in the actual field, why the semiconductor industry is a target for attacks, and how security incidents impact companies. Furthermore, it examines how security threats are evolving as manufacturing environments become more intelligent with the spread of AI and smart factories.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

We will examine the major OT security threats that can occur at production sites in the food and pharmaceutical industries, focusing on real-world cases. You will understand what security issues can arise in smart factories, production facilities, quality control systems, and traceability management processes, and learn basic response methods to prevent production shutdowns and data falsification in a way that is easy for beginners to follow.

This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for job seekers who are vulnerable to AI. Career expert Career D will teach you step-by-step how to apply AI to job searching and career transitions. From basics to hands-on practice, it's designed so that even AI beginners can follow along easily without any burden!

Step-by-step explanations that even beginners can easily understand make coding tests that once seemed daunting clear and approachable. Learn only what you need and apply it to real problems right away!

Do you know the basics but feel overwhelmed when it comes to applying them in practice? Drawing on real-world experience, we make complex LLM architectures easy to understand.

Do you want to make substantial profits even in a bear market? Are you interested in automated trading but unable to get started because of coding, trading strategy design, exchange APIs, and server deployment? In this course, even those new to Python will learn how to use ChatGPT and Codex to turn trading ideas into concrete strategies and implement them through backtesting and live automated trading code. You will practice Binance futures automated trading using Python and CCXT, technical indicator strategies, averaging-down backtests, and a Kimchi Premium strategy based on the Upbit API. You will then apply Telegram notifications and order safety features, manage the completed bot with GitHub, and deploy it to a cloud server. Rather than entrusting all investment decisions to an LLM, you will determine the strategy and risk management criteria yourself, using the LLM as an assistant for strategy design, code writing, and troubleshooting. After completing the course, you will be able to do more than simply run the provided code—you will be able to create, validate, modify, and deploy your own strategies!

This course examines major security threats and incident cases that can occur in the process control environment of the chemical industry, providing an easy-to-understand approach to AI-based anomaly detection and response. Participants will learn practical OT security, focusing on risks unique to the chemical industry such as production shutdowns, manipulation of process values, and hazardous substance leaks.