The current state of AI development as felt through meeting numerous AI companies

This special lecture concurrently prepares for Microsoft AI-900 certification, featuring the latest content reflecting May 2025 exam scope, combining theory and practice, including AI overview, machine learning basics, computer vision, natural language processing, document intelligence, knowledge mining, and generative AI.

Many people use ChatGPT and frequently hear about recommendation systems and autonomous driving, but when asked to explain “why they work the way they do,” they often struggle to find the words. If you only follow coding courses, the code runs but the underlying principles don’t stick. If you only take math courses, you see the formulas but can’t connect them to AI. Overseas courses can feel intimidating because of the English, while introductory courses in Korea tend to focus heavily on hands-on practice. While building real models in AI competitions, running Everyone’s AI, and meeting thousands of learners, I repeatedly saw the same thing: the obstacle wasn’t how to use the tools, but the moment when functions, derivatives, vectors, and backpropagation became disconnected from one another. This course bridges that gap. From how functions define inputs and outputs, to how derivatives determine the direction of learning, and how backpropagation passes errors backward, it explains everything in one continuous flow—from the fundamentals of mathematics to neural networks and softmax. Rather than memorizing formulas or simply copying code, this course helps you understand “why” through equations and intuitive illustrations. For anyone who wants to truly understand AI, it will serve as a solid first step toward moving on to deep learning.

Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.

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.

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.

Artificial Intelligence, AI, agents... They might seem grand, but once you try them, they're not as difficult as you think. That's why it's important to implement simple features yourself. Through practical projects that can actually be used at a company, you'll directly experience various use cases and learn how to utilize and apply AI agents.

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.

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.

■ Course Overview Are you interested in 3D video production but feel it might be too difficult? Or do you want to create unique videos that stand out from the crowd? With CreateStudio3, you can easily create professional 3D animated videos without any coding. In this course, you will learn the basics of video production through step-by-step explanations that are easy for even beginners to understand. Through this course, you will master the basic operations of CreateStudio3 in a short period and become able to create your own original 3D animated videos. ■ What You Will Achieve By taking this course, you will be able to: - Experience and internalize the basic operations of CreateStudio3 through hands-on practice. - Create unique 3D animated videos. - Create highly flexible scenes by moving viewpoints and angles. - Achieve marketing and promotional results using video. - Acquire simple video production skills. ■ Who This Course Is For - Those who tried complex software like Blender but gave up. - Those who feel paid tools like VYOND are too expensive. - Those who want to create videos easily without coding. - Those who want to share unique 3D videos on social media or YouTube. - Those who want to publish videos without showing their face. ■ Required Tools and Costs - A computer *The instructor uses a Mac, but Windows is also supported. - Purchase of CreateStudio3 is required. (Detailed instructions on how to purchase it at a great price will be explained within the course.) Take this opportunity to master CreateStudio and start creating professional 3D animated videos. This experience is sure to be a major plus for your career. The main contents of this course are as follows: - Basic operations of CreateStudio3 - Basic techniques for 3D animation - Creating character animations - How to use effects - Scene settings and video updates - How to move the viewpoint - Video exporting and specific output methods I look forward to seeing you in the course. Hiroshi Wada

How does the architecture change when an LLM is integrated into an existing backend? Going beyond simple LLM API calls, this introductory system design course helps you understand the core components of AI services—such as Model Routers, LLM Gateways, and Vector DBs—and progressively design operational AI service architectures, including RAG and AI Agents. It helps those who want to build their own LLM-based AI services quickly learn the design process.

We will explore the types of applications and web services that can be built using LLMs.

AI is no longer a tool exclusive to developers or experts. The gap between "those who use AI" and "those who don't" is already widening across all roles—from students and job seekers to office workers, planners, and developers. This course is a practical survival guide focused on: ✔️ How to use AI as a tool to explode your productivity, not as a replacement technology ✔️ Prompts you can immediately apply to work, studies, job hunting, planning, and development ✔️ The mindset that turns someone who says "I tried AI, but it wasn't that great" into an AI expert Rather than just explaining features, I will show you: 👉 What kind of people survive in the AI era 👉 Exactly how those people use AI in practice Based on my own experiences and real-world examples.

An introductory AI lecture tailored for those new to artificial intelligence! It easily summarizes core concepts from data to generative AI. The goal is not to build AI, but to achieve a level of practical understanding where you can ask the right questions and explain the technology.

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

Processing actual smart health data held by Daegu Haany University for use in machine learning, and creating customized smart health applications using vibe coding and refined information.

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.

For those of you who have completed intermediate SwiftUI, it is now time to integrate AI into your apps. Complete an on-device AI app that runs locally without an internet connection using Apple Intelligence and the FoundationModels framework.

The Master Guide to AI for Java Developers! This course shatters the prejudice that AI is the exclusive domain of Python and empowers your Java applications with AI-driven eyes, ears, voice, and even coding capabilities. Grow into an AI Architect based on the OpenAI API. You will directly develop various AI experts such as an AI writer, translator, artist, and coding companion. You will also build a multi-functional AI assistant that integrates core features including text summarization, sentiment analysis, image description, Java code generation, speech-to-text/text-to-speech conversion, and image/subtitle generation. This is a golden opportunity to maximize the competitiveness of existing Java systems by learning how to assign AI roles through system messages and even implement harmful content moderation.

🔥Don’t have time to complete the 32-hour all-in-one course? We’ve condensed the four subjects of the Big Data Analysis Engineer written exam into around 4 hours. Connect concepts directly to actual exam questions through modified past exam questions, and receive 150 pages of lecture materials plus 13 pages of final review notes for the exam room.