Understanding AI Literacy

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

Let's develop the capacity to extract valuable information from big data and support decision-making!

Let's analyze and visualize data and learn machine learning concepts using Orange 3!

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

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

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

Let's design, implement, and develop while learning the basic concepts of the C++ language and object-oriented concepts!

ChatGPT, become a creator using generative AI!

Let's learn various data structures and algorithms and develop practical skills by implementing them through programming!

Let's build a solid foundation in Python and solve data analysis problems!

Let's look into how to deploy Abyss for non-majors!

Let's understand model algorithms for machine learning and deep learning by utilizing Keras!

Let's understand the main algorithms of machine learning and deep learning, and learn about artificial intelligence!

Modern C++ programming based on object-oriented concepts for computer science majors

Let's manage projects efficiently and smartly through data science

Are you a digital talent interested in coding and development? Get started with block coding through App Inventor!

Let's develop practical data-driven administrative capabilities to empirically solve administrative and policy problems by analyzing public data with R and Python!

Let's develop basic field knowledge of clothing science and the capabilities of a fashion specialist through understanding AI-based textile CAD!

**"AI Philosophy - Ethics and Challenges in the Age of Artificial Intelligence"** is a topic that deals with the ethical and philosophical exploration of the development of artificial intelligence (AI) and its impact on human society and culture. This topic goes beyond simple technological development and delves into how AI affects human life and what ethical decisions we should make accordingly.

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 gain a broad range of knowledge, from establishing AI-based system testing strategies to designing and executing test cases, as well as utilizing AI for test support. This course is based on the ISTQB AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

[The 2nd edition is scheduled for completion in 2026] You can develop your programming skills while exploring the fundamental principles of Large Language Models (LLMs) such as ChatGPT and Claude in depth. You can learn a variety of information and development techniques that are often difficult to come by.

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.

This course is ideal for those who want to focus on theory and context rather than practice, aiming to organize their knowledge of deep learning in depth and grasp the big picture. It makes the mathematical and statistical foundations of deep learning easy to understand and provides intuitive interpretations of key modern models—such as AutoEncoder, GAN, Transformer, and AlphaGo—from a developer's perspective.

"Prepare for the future talent who will lead the AI era, right now!" Artificial intelligence (AI) has now become a core technology that brings innovation to our lives and industries. As various companies and institutions actively adopt AI technology, the demand for related jobs is rapidly increasing, which is also a great opportunity in the job market. However, many people feel at a loss about what and how to prepare to enter the AI field. The "AI Job Roadmap" e-learning course provides systematic and practical job strategies for job seekers, career changers, and non-majors who want to enter the AI field. It summarizes everything about the AI field, from basic concepts to practical projects and job preparation. Through this course, you can build a solid technical capacity in the AI field and complete your own powerful portfolio to grow into a key talent needed in the AI industry.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

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.

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 everything from core recommendation system algorithms to practical implementation. - Content-based filtering - Collaborative filtering and deep learning-based recommendation model implementation - Two-step recommender systems implementation - Hands-on practice using PyTorch/RecBole - Industry know-how and recommendation result visualization

Using AI tools, you can generate human photos and turn them into talking videos.

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

As AI technology rapidly advances, the nature of existing jobs is changing and new opportunities are being created. Accordingly, not only technology-centered jobs such as data analysts, AI engineers, and cloud architects, but also hybrid jobs such as AI ethics experts, digital twin designers, and sentiment data analysts are attracting attention. In addition, creative job groups that utilize technology, such as EdTech experts, digital healthcare consultants, and virtual reality creators, are also emerging. As AI becomes a tool that assists and expands human work, talent with continuous learning ability and creative thinking will become a key factor in achieving success.

A comprehensive compilation of approximately 130 ML/AI engineer interview questions and answers learned through about 20 interviews

AI is no longer a tool exclusive to developers or experts. The gap between "those who use AI" and "those who don't" is already widening across all roles—from students and job seekers to office workers, planners, and developers. This course is a practical survival guide focused on: ✔️ How to use AI as a tool to explode your productivity, not as a replacement technology ✔️ Prompts you can immediately apply to work, studies, job hunting, planning, and development ✔️ The mindset that turns someone who says "I tried AI, but it wasn't that great" into an AI expert Rather than just explaining features, I will show you: 👉 What kind of people survive in the AI era 👉 Exactly how those people use AI in practice Based on my own experiences and real-world examples.

This course is designed for those who use AI but are confused about how much they can trust it. It covers how to use AI in your work or creative process without overdoing it, ensuring it provides actual value. Rather than requiring professional development knowledge or complex tools, it focuses on how anyone can effectively integrate AI into their own workflow. Instead of teaching complex prompt engineering, the course focuses on the mindset of **knowing when to use AI and when it's better not to**, as well as **how to verify and refine AI outputs** rather than trusting them blindly. Through this course, you will establish criteria for using AI not as an automation tool that replaces everything, but as a **practical partner** that helps organize your thoughts and assists in your work.

Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.

This introductory course for AI engineers is designed to provide a brief hands-on experience of the entire process, from data processing and model development to cloud, MLOps, and ethical considerations. It focuses on building practical skills by helping students understand the process of connecting models to actual services, rather than just creating them. The course includes hands-on exercises and examples so that even those learning AI for the first time can easily follow along.