Edge Computing Fundamentals and Applications: From Concepts to Practical Implementation Strategies

Nationally Certified Industrial Security Manager: "Final update of the newly renewed version is complete"!! The 2026 exam schedule is expected to be announced between February and March on the following site (https://license.kaits.or.kr/license/web/board/brdList.do?menu_cd=000021). This course is designed to help you obtain the Nationally Certified Industrial Security Manager certification by providing a systematic understanding of industrial security from a management perspective. Rather than focusing on rote memorization, the content systematically organizes the concepts, structures, and flows of industrial security so that even non-security majors can understand it, preparing you for the exam while also supporting practical work and career expansion.

This is an online course where you can learn essential content for certification, from basic concepts of information security to the latest security issues. With theory reflecting the latest exam trends and practical mock tests, you can efficiently prepare for the exam, and it's structured so that even those new to information security can easily follow along.

This course is designed for those aiming to obtain the Data Architecture Semi-Professional (DAsP) certification. It provides a simple and systematic overview of essential exam topics, ranging from basic data architecture concepts to data modeling, data quality, and governance. The curriculum is structured to minimize complex theories and focus on frequently tested concepts, making it accessible for non-majors and beginners to learn without pressure. Build your fundamental skills in understanding data structurally while preparing for the DAsP certification.

AI Tech DNA Series: Core Computer Fundamentals from an AI Perspective is an introductory course designed to help you understand the basic concepts of computers needed in the AI era in the easiest way possible. It explains fundamental principles such as CPU, memory, storage, networks, and data structures by connecting them to real-life analogies and AI perspectives, building a solid foundation to advance into Python, AI, security, and cloud.

[Reflecting the latest related regulations and guidelines presented by the Korea Financial Security Institute, Financial Supervisory Service, and Personal Information Protection Commission] In the rapidly changing digital financial environment, security has become not an option but a core survival strategy. This course covers the new directions of financial security changing with digital transformation, strategic response methods, and practical approaches to establishing a security culture within organizations. We will examine the policy directions of the Korea Financial Security Institute, the latest regulatory trends, and global security trends together, learning security innovation strategies centered on people and organizations beyond technology-focused approaches.

[Reflecting the latest related regulations and guidelines presented by the Korea Financial Security Institute, Financial Supervisory Service, and Personal Information Protection Commission] This is a course where you learn how an organization's security governance and internal control systems should operate through actual financial security incident cases. You will analyze the causes of incidents and response processes, and based on this, learn effective security policy establishment, risk management, and compliance response methods. The goal is to build security culture and control systems across the entire organization, going beyond technical responses.

Welcome to the R Programming Basics course! This course provides an easy and systematic guide to the core concepts of R programming and practical data handling and visualization methods for those starting out in data analysis. Starting with R installation, it covers data structures, basic syntax, and real analysis cases, aiming to help you successfully take your first step as a data analyst.

The AWS Certified AI Practitioner practice exam course is a core summary program for passing the certification. First, you'll quickly review the fundamental concepts of AI/ML and generative AI, and learn about the features and use cases of AWS's major AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you'll practice determining which AI solutions are appropriate for various real-world problem scenarios, and also cover content related to responsible use of AI models and data security. Finally, you'll learn problem-solving strategies by question type and prepare for the exam through practice mock tests. Through this course, you can efficiently prepare for the exam in a short amount of time.

What do you learn in the 'Business Information Visualization Certification' course? This certification course focuses on developing the ability to analyze data well, visualize it in an easy-to-understand way, and clearly and effectively communicate the information needed when making important decisions in a company or organization. Simply put, it's a course where you learn the skills to not just look at data, but to discover the hidden meanings within it and express them through pictures, tables, graphs, etc., so you can explain them well to others. Through this course, you will: Develop the ability to think strategically through data, build practical skills that can be immediately applied to actual work, and enhance your professional expertise and competitiveness. Through this lecture, develop the ability to connect business and data, and take one more step toward becoming an expert who understands and explains data.

Computational thinking isn't something that only computer science majors learn. Every profession has problems that need to be solved, and computational thinking can be used to solve those problems.

This course is designed for those who wish to obtain the nationally certified Associate Data Analyst (ADsP) certification. At a time when there is a need to cultivate practical data analysis professionals in both public and private sectors by objectively verifying data analysis skills essential for data utilization across society, this course is structured to enable participants to develop the necessary competencies and take the qualification exam to obtain the certification.

This course is designed to help students easily understand the concepts of the Internet of Things (IoT) while simultaneously preparing for the IoT Knowledge Proficiency Test certification exam.

This course is designed to simultaneously develop both fundamental theory and practical application skills needed to proficiently execute AI modeling projects in real-world settings. Learners will understand the overall flow of AI projects and experience step-by-step processes through hands-on practice: problem definition → model design → data acquisition and preprocessing → feature extraction → model training and validation. Additionally, by learning how to select and manage optimal AI models in various situations, learners can build practical AI capabilities that can be applied to actual business environments. Through this course, learners can systematically understand the entire AI modeling project process and strengthen their data-driven problem-solving abilities based on this foundation.

The AWS Certified AI Practitioner practice exam course is a core summary program for passing the certification. First, you'll quickly review the fundamental concepts of AI/ML and generative AI, and learn about the features and use cases of AWS's major AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you'll practice determining which AI solutions are appropriate for various real-world problem scenarios, and also cover content related to responsible use of AI models and data security. Finally, you'll learn problem-solving strategies by question type and prepare for the exam through practice mock tests. Through this course, you can efficiently prepare for the exam in a short amount of time.

"Your first step to creating a customized LLM with LoRA-based lightweight fine-tuning!" This is an introductory hands-on course designed so that even those new to LLMs can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading the model → applying data → training → comparing results. In a short time, you'll directly experience the workflow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, and gain an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

GCP (Google Cloud Platform) is Google's cloud computing service, offering a variety of infrastructure and platform services. This allows you to leverage various functionalities.

This training will help you understand the world-famous cloud, build your own cloud environment, and strengthen your ability to use it easily.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.

This course will teach you step-by-step the principles of Amazon Web Services (AWS) cloud computing and how to use core services through various practical exercises.

An introductory course tailored for beginners that systematically teaches you how to build AWS core services and infrastructure! You can naturally learn the basics of the cloud and how to use AWS through hands-on practice.

AWS CLF (Certified Cloud Practitioner) is an introductory course that allows you to build basic knowledge of the cloud. By increasing your understanding of AWS cloud technology and services through this certification, you can move on to more specialized certifications in the future and build the basic capabilities necessary for cloud-based development and operations.

No more 'Question - Answer - Read-through' explanations! We explain all the knowledge related to how to solve AWS SAA certification exam questions!

This explains the foundational principles of large language models like ChatGPT with a focus on theory.

Create high-quality AI videos with Midjourney&Runway. Director Kim Dong-ah, who collaborated with Samsung, will personally guide you step-by-step through the AI video production process based on a virtual brand.

Stop accessing localhost! Let me deploy to AWS too!

Learn cloud infrastructure automation technology using AWS and Terraform, and practice efficient infrastructure management and deployment. Manage AWS resources as code through Terraform, and learn how to deploy consistent infrastructure across various environments.

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.

This course covers the entire process of evolving ChatGPT from a simple conversational AI to an intelligent AI Agent that performs actual work tasks. Using three core frameworks - LangChain, LangGraph, and LangSmith - you'll directly create AI Agents that can be immediately used in real-world applications.

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.

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 comprehensively learn everything from establishing AI-based system test strategies to designing and executing test cases, and even methods for utilizing AI to support testing. This course is conducted based on ISTQB's AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

Master AWS networking completely! Learn VPC, subnet, routing, and security with a focus on practical application, and design secure and scalable cloud network architectures. Complete the core skills that every working engineer must know in a short period of time!

Leverage Python to learn machine learning techniques, improving real data information extraction and prediction model development skills!