This course aims to understand various security threats occurring in information systems, particularly in internet environments, and to learn core security technologies to protect against them. Focusing on key cryptographic techniques such as symmetric and asymmetric key cryptography, the course is structured to provide a systematic understanding of the overall flow of information security, including the underlying mathematical concepts of cryptography.

Students will learn the fundamentals of digital circuits, including Boolean logic, logic gates, circuit simplification, state machines, and Register Transfer Level (RTL) design. Additionally, students will learn design methods using Verilog.

This is an introductory lecture designed to help you understand the core concepts of non-invasive EEG-based Brain-Machine Interfaces (BMI) and the process of Motor Imagery-based signal processing. It provides an easy-to-follow explanation of the entire workflow, from the basic principles of EEG signals to Motor Imagery experiments, data processing, and how actual BMI systems operate.

Building a Full-Stack System Without Coding: Complete the entire pipeline from data collection to AI/ML analysis and web dashboards using only Korean prompts (Vibe Coding). Owning a 100% Automated Pipeline: Secure an independent stock analysis tool that sends S&P 500 screening and investment opinions via Telegram every morning. Acquiring a Practical Data-Based Investment Framework: Master institutional-level data analysis and risk management capabilities based on source code currently in actual operation.

Drawing from my own experience of feeling despondent when trying to implement practical code during my first MSA transition—despite knowing the theory—I will help you grow into a developer who guarantees perfect data consistency amidst any system failure by directly rolling back daunting compensation logic through 9-step practical patterns and AI Agent coding.

This is a lecture on implementing various artificial neural networks using PyTorch, a deep learning framework with very high utility in the field of artificial intelligence.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

When you learn machine learning, you learn how to improve accuracy. But the moment you try to put that model onto an actual chip, questions no one has answered remain. How many multiplications does this model perform? How much does it need to remember, and for how long? Can the chip specifications you are targeting handle those requirements? Machine learning textbooks talk about accuracy, and semiconductor textbooks talk about circuits, but materials that bridge the gap between them are rare. I repeatedly encountered this gap while implementing RISC-V CPUs and NPUs on FPGAs. The model with the highest accuracy often turned out not to fit on the board. In this course, you will build six algorithms directly in Python, measuring the number of multiplications, comparisons, memory usage, and accuracy each time. Then you will convert those figures into the resources of an actual FPGA board. Saying that something requires a certain number of multiplications is not enough to gauge its size, but knowing that it uses a certain percentage of the board makes the decision clearer. After nine Labs, when the six models are brought together in a single table, an unexpected picture emerges. We spent nine lessons counting multiplications, but multiplications were not what held us back. After that, we reduce floating-point values to integers, manage bit widths, and even establish criteria for evaluating the circuit. You do not need an FPGA board. The course is conducted entirely in Python, and the board is used only as a reference for converting the measurements.

You can acquire an overview of machine learning and deep learning, how to use basic tools, and the Python language knowledge necessary for learning in a short period of time.

A course chosen by 3,000 students! Updated to GPT-5 version! How far can you go with ChatGPT? Create automated stock trading applications and web investment reports!

This is a course on building your own stock and cryptocurrency automated trading programs using ChatGPT, even without prior coding knowledge. You will gain both AI development skills and financial investment knowledge through hands-on practice covering the entire process, from data collection to predictive model development, stock recommendation systems, and actual automated trading.

In an era where flexible data processing beyond the limits of SQL is required, learn everything about MongoDB. From NoSQL concepts to installation, CRUD practice, aggregation pipelines, text search, and indexing, you will learn step-by-step and complete your practical skills through Python crawling integration and container environment construction.

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.

This course aims to cover the latest Gemini API SDK (@google/genai) in a Node.js and TypeScript environment. You will learn how to use multimodal technology to process text, images, and video simultaneously. We will practice the entire process, from issuing an API key to project setup and model calling.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

This course trains your frontend system design mindset through real-world service cases such as Threads feeds, Amazon shopping carts, Netflix streaming UI, Google Docs collaborative editing, Micro Frontends, Agentic UI, and Observability.

Building an MVP with AI is no longer difficult. However, most projects stop at the next stage. 👉 You’ve built the features 👉 But development doesn't continue Why does this happen? The problem isn't the code; 👉 It's because there is no structure that allows AI to work continuously. --- In this course, based on an existing project, 👉 We will cover the process of building a structure 👉 That allows AI to continue development on its own. --- Instead of simply using AI tools, we will: * Create a docs structure * Define the SSOT (Single Source of Truth) * Execute development on a per-ticket basis * Connect QA and iteration cycles 👉 To complete a single "AI Development System." --- Through this process, you will: 👉 Create a structure where development continues 👉 Even without a human manually coding. In other words, you can: 👉 Build and understand a development system 👉 That operates AI like a team. --- This course is designed for: 👉 Those who want to build a structure applicable to their projects immediately 👉 Those who started development with AI but found it difficult to sustain 👉 Those who want to move to the next level after "Vibe Coding" --- Beyond just learning, we provide an experience where you: 👉 Take action 👉 Build a structure that actually works 👉 And walk away with a framework you can apply to your own projects.

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.

This is a course to learn about Airflow, an Orchestration tool for efficiently building and managing data pipelines. Welcome to the Airflow Master Class, where even beginners can learn step-by-step!

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.

We introduce methods for planners and marketers without data analysis experience or technical skills to try data analysis at the most basic level, complete with various examples. Built on years of hands-on practice with over 2,000 participants in more than 100 companies and public institutions, the content is designed around the most practical analysis methods for data non-experts.

Build your own powerful stock price analysis model that analyzes over 40 types of economic indicators and stock price data using AI to predict not only the S&P 500 and QQQ ETFs but also individual stocks!

This course is a practice-oriented lecture that goes beyond 👉 just explaining the concepts of RAG (Retrieval-Augmented Generation), 👉 to building the actual working architecture yourself, 👉 and experiencing expansion and optimization. Starting from simple RAG examples, you will learn step-by-step—from Advanced RAG to Modular RAG and Agent-based RAG—at a level that can be immediately applied in the field.