머신러닝, 딥러닝 기초 with Python, Keras

Basic manners, etiquette, and communication skills education to foster global leaders leading the 4th industrial revolution era

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

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

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

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

Learn and understand AI and AI ethics, then integrate with your major to boost AI digital skills!

Let's build a foundation of MATLAB and apply and understand the basic concepts of programming!

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

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

Let's collect, analyze, and communicate data using techniques that handle data 'appropriately' and 'fairly'!

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

Experience developing applications collaboratively in a Linux shell & open source software environment, and build the development environment required for program coding!

Let's understand data analysis suitable for advanced retail business and learn how to utilize tools utilized in the industry!

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

Let's learn various data structures and algorithms and develop the ability to implement them through programming!

Learn basic website building methods and gain practical application skills from the basics of web development through practical projects linked to public data Open API!

Let's understand and try policy evaluation with R and R Studio!

Let's manage projects efficiently and smartly through data science

Let's understand data analysis methods using Python, analyze and visualize various types of data on our own, and organize an outline of our data story!

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

DNN, CNN, RNN? This lecture perfectly organizes the core algorithms of deep learning and puts them into practice through practical deep learning training, even with difficult-looking technical terms!

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

Let's implement a deep learning framework directly with Excel! Let's solve supervised learning/unsupervised learning/reinforcement learning with the implemented framework!

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

From the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

This course is an introductory program designed so that learners who are new to AI technology can easily understand and follow along. Through the lectures, you will learn the basic concepts and usage methods of AI platforms, and conduct hands-on practice directly generating images using various AI tools. Upon completing this course, you will become much closer to AI and acquire the capability to create AI images that can visually implement creative ideas.

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

Through this course, students will learn various reinforcement learning theories and implement them themselves, as well as create a reinforcement learning environment to test the reinforcement learning algorithm implemented using Unity Machine Learning Agents.

This course is a comprehensive program that covers everything you need to know to utilize generative AI in practical work settings, from the basic principles of LLM (Large Language Models) to RAG (Retrieval-Augmented Generation), and even the latest technologies like AI Agent and MCP (Modular Command Protocol). It is structured to naturally teach you how generative AI understands, searches, judges information, and extends into AI Agents that take action, following the flow of technological development.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

This course explains the basic concepts of LLM and GPT in an easy-to-understand way for everyone. Students can directly use the GPT API to create chatbots and run them on the web using Streamlit. By experiencing everything from basics to hands-on practice, you can solidly establish your first steps in AI utilization.

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.

This course starts with the question "If I had been on the Titanic, could I have survived?" and completes a full-stack project that develops an AI model to predict survival probability based on actual data and serves it as a web service. You'll practice the entire process of AI and web development, from deep learning modeling using PyTorch, building a backend server with FastAPI, to implementing a user interface with Next.js.

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 :)

From Multi Head Attention to the Original Transformer model, BERT, and Encoder-Decoder based MarianMT translation model, you'll learn Transformer inside and out by implementing them directly with code.

The PyTorch_Project Edition, understood instantly with code, implements practical deep learning projects using image, video, and NLP data, understanding model structure and flow through code-centric learning over theory.

If you want to be recognized as a machine learning expert based on large-scale data, from understanding the core framework of Spark machine learning, to SQL-based data processing through difficult practical problems, to data analysis through business domain analysis, and to the ability to implement optimized machine learning models, please join this course.