Kaggle Competition Project Practice

This is a process for completing IoT products without complex coding, using the Vibe Coding methodology powered by AI agents. You can experience the entire product development cycle in a condensed format—from embedded hardware control and AI vision recognition to PCB design, 3D printing, and web/app service development—allowing you to launch functional, commercial-grade IoT devices.

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

Are you simply telling Codex, “Build it for me”? It works well at first. But as the project grows, the AI modifies the wrong files, forgets the rules, and repeats the same mistakes. In this course, you’ll learn how to use the **latest Codex** to delegate coding while keeping control over **design, permissions, context, and verification** as a developer. **Design → Plan → Implement → Test → GitHub PR** Based on the developer’s judgment and review, AI development automation is applied throughout this entire process.

The era of Physical AI, as mentioned by Jensen Huang in 2025, is coming—alongside Perception AI, Generative AI, and Agentic AI. Experience Physical AI firsthand, quickly and easily. Explore Physical AI using Hugging Face's LeRobot library and actual physical robots.

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.

In the AI era, web developers need more than coding skills—they need the ability to use AI to turn ideas into real-world results. Build your AI web development skills for practical work and portfolios by gaining hands-on experience creating UIs with Stitch and Figma Make, implementing them in React, and deploying them.

Are you still coding alone? We are now in an era where AI handles 99% of the work. Instead of memorizing complex syntax, this course teaches you how to turn Google's powerful AI, 'Gemini Pro,' into your 24-hour AI development partner. You will learn the fundamental principles of Flutter using the paid Gemini Pro model for free and turn your ideas into reality through professional-level projects.

This lecture is designed for job seekers preparing for Evaluation and Analysis roles in Samsung Electronics' DS Division (Memory, S.LSI, Foundry, TSP, AVP) and PE, AE, and Solution PE roles at SK hynix, who are struggling with the differences between business units and job functions. You will learn how to categorize job titles by company based on the actual workflow of Product Evaluation roles and how to translate your major-related experiences into professional terminology suitable for resumes and interviews. We will help you establish an application strategy by connecting experiences in Analog circuit design, Verilog/FPGA, process experiments, and data analysis with key industry terms such as Yield, Wafer Map, Shmoo Plot, and Failure Analysis.

To design AI semiconductors such as NPUs, transformer accelerators, and mini LLMs yourself, you need to understand theoretically why the computations inside them occur. This course distills and condenses into three parts only the essential theory required for hardware design, covering everything from a single neuron to CNNs, transformers, and LLMs. Rather than memorizing formulas, a professor with 30 years of experience in the semiconductor industry connects software theory with hardware implementation through an intuition for “why it works that way.”

An era where even IT beginners can become the 'CEO of their own platform' with just an idea, utilizing AI and Gnuboard! We will demonstrate the actual development process in detail, from planning to deployment, and even share various monetization methods such as advertising and shopping malls. Start your online business right now!

Document (SDD) → Code Automation. Make the system work instead of typing prompts. Build your own AI development agent with Skills, Sub-agents, and Commands, and complete monetization services through 5 real-world projects.

Now you can use Python in Excel! A light lecture to try out the latest features!

This course is a hands-on masterclass that completely dissects the core technological evolution of generative AI, from LDM (Latent Diffusion Model) to DiT (Diffusion Transformer). We directly analyze the latent space-based learning principles of LDM, the structure of Stable Diffusion, and the implementation methods of the latest Diffusion Transformer through papers and code. Students will systematically learn the latest trends and structural evolution of generative models by directly implementing LDM, CFG (Classifier-Free Guidance), and DiT models using PyTorch.

Now your imagination becomes the ultimate game design document! With AI, you can have fun chatting as if you were building with LEGO and complete your first game. Try Google Gemini Pro for free!

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

Now we need to move beyond the beginner level and reach the level of a professional developer. I’ll reveal how games are actually made in the industry.

Essential certification for the AI era, MS AI-900! 🚀 Did you know? ChatGPT operates exclusively on Microsoft Azure! If you want to properly utilize Microsoft Azure OpenAI, which exclusively provides the latest GPT models, now is the perfect opportunity. Grow into an Azure AI services expert through the AI-900 course and master enterprise-grade AI solutions that companies trust. Secure global official certification and enhance your competitiveness as a true AI professional!

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

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."

Theory, numerical approximations, intuition, and visualization in integral calculus. Enhance your math-coding skills.