AI Finally Gets a Body - What is My Survival Strategy in the Age of Robots? Physical AI is not just about robots. It is an overthrow of the economic paradigm created by the grand convergence of artificial intelligence, robotics, and energy technology. This course explores various perspectives, from the background of Physical AI's emergence to the strategies of global big tech, hardware sovereignty, and future social issues such as robot taxes, basic income, and global inequality.

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.

Learn the core concepts and operating principles of Physical AI, which moves beyond the screen to be implemented in robots, autonomous vehicles, and drones. Understand the sensing-perception-action mechanism, digital twin-based learning, and the importance of embodied data, while exploring the global technological competition and Korea's strategic direction through real-world cases in industries such as manufacturing, mobility, and agriculture.

You can transform your ideas into beautiful presentations in just a few minutes. No more spending hours struggling with slide design. With GAMMA's AI technology, you can dramatically improve your content creation process.

Complete Understanding of Robotics High- and Low-Level Controllers, Sensors, and Ultra-High-Speed Communication Concepts Through the Unitree Go2 Example

You will learn about Transformers inside out by directly implementing everything from Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder-based MarianMT translation model, and the Vision Transformer in code.

You can enhance your development capabilities by deeply exploring the fundamental principles of large language models like ChatGPT and Claude. You will be able to learn a variety of information and development techniques that are not commonly encountered.

Putting a neural network on an FPGA—the phrase is familiar, but few have actually done it. If you want to stay a step ahead in capstone projects, competitions, or graduation projects, you must be able to go beyond just training a model and actually build and prove how those computations run inside a real chip. This course bridges that exact gap between theory and physical hardware. You will complete a neural network accelerator (NPU) for MNIST digit recognition from start to finish—from reading specifications to Python golden models, Verilog RTL design, and FPGA verification. From Conv layers made with line buffers and parallel MACs, through ReLU, MaxPool, and Flatten, to fully connected layers and Argmax—you will integrate nine blocks into a single chip and prove for yourself that "the Python reference and the hardware output do not differ by even a single bit (Bit-True)." I have even included how to overcome those frustrating moments when the simulation runs fine but the results are subtly different. I will guide you through practical know-how that general deep learning textbooks don't cover, such as integer quantization, array axis reordering, and accumulator overflow prevention. I have distilled the trial and error I experienced over years of RISC-V CPU design and FPGA Bit-True verification into this course so that you don't have to repeat them. By the end of the class, you will have a completed hardware project that allows you to say, "I designed and verified it myself."

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.

In the era of AI and Big Data, are you utilizing your organization's data effectively? This course builds essential capabilities for reading and interpreting data, covering everything from the foundations of statistical thinking to the core principles of machine learning and deep learning. Grow into a practical leader capable of discovering patterns amidst volatility and making data-driven decisions.

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.

A general education lecture for the public to shed the vague fear of artificial intelligence. Through concrete examples, we learn what AI learning truly means. Also, via specific examples, we examine AI's 'brain structure' and how it thinks.

■ 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

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.

Have you been getting stuck on linear algebra formulas every time you try to study AI? Instead of memorizing formulas, this lecture shows you visually how vectors and matrices actually move in space. By the end of the course, you will be able to interpret the mathematics behind neural networks, PCA, and SVD on your own.

In the AI era, developers must become “integrators,” not mere coders. This course covers how to combine Unreal Engine with the latest AI tools, such as ChatGPT and Claude, throughout the actual C++ development process. Through practical examples designed by YAL, an Unreal-certified instructor, you will build a development environment where AI generates, analyzes, and assists with code, and complete a next-generation C++ workflow that integrates AI with Unreal.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

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.

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.

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.