AI-Enabled Digital Transformation

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

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

ChatGPT, become a creator using generative AI!

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

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!

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

Let's build the skills to develop web applications using React and cultivate the capability to apply them in practice!

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

Are you a digital talent interested in coding and the Internet of Things (IoT)? Get started with programming through MicroPython!

Are you a digital talent interested in the Internet of Things (IoT)? Get started with the Internet of Things through Arduino!

Learn how to use Git and GitHub and use them for collaboration!

Experience text coding through block coding and control Arduino!

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

Java programming based on object-oriented concepts for computer science majors

Let's learn how to translate real-life and major problems into actual computer programs and practice using Python-based artificial intelligence tools!

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

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

Understand and learn about Artificial Intelligence and AI ethics, and strengthen your AI digital capabilities by integrating them with your own field of study!

It improves logical thinking skills and cultivates the ability to integrate one's major with information and communication technology in the era of the 4th Industrial Revolution.

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

The AWS Certified AI Practitioner practice exam course is a core summary program designed to help you pass the certification. First, you will quickly review the basic concepts of AI/ML and Generative AI, and learn the features and use cases of key AWS AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you will practice determining which AI solutions are suitable for various real-world scenarios, while also covering topics related to the responsible use of AI models and data security. Finally, you will learn problem-solving strategies for each type of exam question and prepare for the actual test through mock exams. This course allows you to prepare for the exam efficiently in a short period of time.

You can benchmark manufacturing innovation methods for semiconductors and run machine learning and deep learning with semiconductor data without coding.

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!

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.

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 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.

The Master Guide to AI for Java Developers! This course shatters the prejudice that AI is the exclusive domain of Python and empowers your Java applications with AI-driven eyes, ears, voice, and even coding capabilities. Grow into an AI Architect based on the OpenAI API. You will directly develop various AI experts such as an AI writer, translator, artist, and coding companion. You will also build a multi-functional AI assistant that integrates core features including text summarization, sentiment analysis, image description, Java code generation, speech-to-text/text-to-speech conversion, and image/subtitle generation. This is a golden opportunity to maximize the competitiveness of existing Java systems by learning how to assign AI roles through system messages and even implement harmful content moderation.

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.

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 can transform your ideas into beautiful presentations in just a few minutes. No more spending hours struggling with slide design. With GAMMA's AI technology, you can dramatically improve your content creation process.

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 :)

Artificial Intelligence, AI, agents... They might seem grand, but once you try them, they're not as difficult as you think. That's why it's important to implement simple features yourself. Through practical projects that can actually be used at a company, you'll directly experience various use cases and learn how to utilize and apply AI agents.

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

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

"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!

If you're planning to learn Python, pay attention to this course!!! It's completely free~ I highly recommend it for preliminary learning before taking formal courses or starting personal study.

[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.

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 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.

In the era of AI, developers must become "integrators" rather than mere coders. This course covers how to combine Unreal Engine with the latest AI tools like ChatGPT and Claude into the actual C++ development process. Through practical examples designed by Unreal Authorized Instructor YAL, you can build a development environment where AI generates, analyzes, and assists with code, completing a next-generation C++ workflow that integrates AI and Unreal.