CloudNet@ - Enterprise LLM Security Guide

Understand the security configurations of major AWS services through architecture diagrams, and gain a practical understanding of how they work by verifying them firsthand through hands-on exercises and security scenarios.

Learn the core techniques of 'Prompt Engineering' to get exactly the answers you want from AI. From a complete beginner's first steps to expert practical applications, maximize your AI utilization skills!

- Public and private sector top-tier information security and personal information protection management system certification audit training in Korea - Preparation for ISMS-P certification strengthening due to comprehensive information security measures establishment - Management system GAP assessment and improvement plan development training - Individual training for ISMS-P initial audit, follow-up audit, and renewal audit - Professional information security training for acquiring excellent information security level enterprise certification

Learn the core techniques of 'Prompt Engineering' to get exactly the answers you want from AI. From a complete beginner's first steps to expert practical applications, maximize your AI utilization skills!

Explains why LLMs are needed, along with their technical background and basic concepts, for those responsible for LLM planning and LLM application planning.

Do you want to effectively use GitHub Actions in real life? This course introduces practical CI/CD scenarios, modularization and version management methods, and also teaches you how to deploy in a cloud environment. Let's learn the most realistic way to use GitHub Actions based on practical experience!

You use ChatGPT, but… Have you ever found it difficult to explain why it gives the answers it does? “I know terms like RAG, agents, and fine-tuning, but I can’t explain them precisely.” “When I hear LLM-related terms, I don’t know what to say.” “I’m always vague when explaining concepts in AI meetings.” This course was created for people just like you. It’s a theory course designed to help you understand LLMs as a “structure,” not just a “tool.” Rather than teaching you how to use ChatGPT or Gemini, it gives you a framework for explaining why they work the way they do.

Records remain, and responsibility grows! Everything about digital ethics that protects the workplace This course explores digital hate, digital sex crimes, and the risks of using AI that can actually occur in the workplace through case-based stories, clearly explaining what the problems are and how to prevent and respond to them. It firmly establishes the standards of digital ethics that today’s employees—who communicate digitally and use AI as part of their everyday work—urgently need, including how to work while respecting one another in digital spaces and how to use AI more safely and responsibly.

This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

We implement the latest Transformer-based PixArt and lightweight adaptation SANA step by step from theory to code. Building on DDPM·DDIM·LDM·DiT covered in Parts I·II, we complete hands-on practice including text encoder integration, samplers (DDIM/ODE), v-prediction/CFG tuning, and small-scale data style fine-tuning.

Build your own customer support agent team with the OpenAI Agents SDK, scaling from one agent to seven. For each feature, trigger real-world incidents and learn to prevent them with code. Cover all ten items in the OWASP Agentic Top 10 across 65 lessons, including tool permissions, guardrails, PII masking, human approval, code execution sandboxes, MCP, and kill switches.

Build a customer support agent from scratch that finds and answers from documents, selects tools to look up information, and actually creates approved tickets. Verify through real execution logs that each task is completed exactly once and through to the end, even if responses are interrupted or the same request arrives again.

As the adoption of generative AI accelerates, new security threats such as corporate confidential information leaks and prompt injections are surging. This course covers strategies for embedding security throughout the entire AI lifecycle, based on the National Intelligence Service (NIS) guidelines' 30 core security measures and 15 practical threat cases. It also addresses security issues in the latest AI trends, such as Agentic AI and Physical AI, and presents methods for establishing governance frameworks that can be immediately applied in practice.

I sent the same request twice and got different answers. Which one can I use in my program? We’ll walk through actual API call logs on screen, step by step, examining the structure of requests and responses, structured outputs, streaming, tool calls, errors and retries, and costs. Instead of treating the mere arrival of text as success, we’ll establish criteria for accepting or holding a response based on its status, format, evidence, and cost.

This is a hands-on deep learning course where you learn by directly practicing the GitHub example code from *Deep Learning with Python, Third Edition* by François Chollet, the creator of Keras. You will implement everything step by step, from basic artificial neural networks to the latest LLMs and diffusion models, while learning machine learning pipelines and best practices that can be applied directly in real-world projects.

Fast is dangerous, and safe is slow? Not true. Let's create a fast and safe pipeline!

Using AI has become easier, but model cards and papers are still difficult to read, even just a few lines. Although you can look up the meanings of individual words, it’s not clear how those words connect to one another. This course builds up around 160 essential terms that frequently appear in AI documents, in the easiest order to understand them, so that in each lesson you can accurately read a single sentence from an actual document.

“Take the first step toward creating your own customized LLM with lightweight LoRA-based fine-tuning!” This course is an introductory hands-on course designed so that even those who are new to LLMs can follow along easily. With complex theory kept to a minimum, it guides you step by step through the entire process: loading a model → applying data → training → comparing results. In a short amount of time, you’ll directly experience the workflow of modern lightweight fine-tuning techniques such as LoRA and QLoRA, and gain an intuitive understanding of “how LLM fine-tuning actually works.” Even without extensive resources, experience the sense of accomplishment that comes from creating an LLM specialized for your own domain!

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.

From analyzing the encryption mechanisms of ZIP, PDF, and MS Office files to hands-on dissection of the WannaCry ransomware, master static analysis tools and GPU-accelerated cracking techniques. This is a practical, security engineering-focused course that builds incident response capabilities through the development of next-generation malware analysis pipelines using OpenAI Codex and automated report generation.