Course Name

LLM Basics and Applications

Summary

Lecture Objectives

• With today’s advancements in artificial intelligence, we are seeing impressive AIs capable of human-level dialogue and task processing through Large Language Models (LLMs). This course focuses on the development process of LLMs, covering core technologies and practical applications, while fostering real-world application skills through hands-on practice. This course is offered in Korean and English, on a biennial basis.

Course Name

Parallel Computing for Developing Large Scale AI Models

Summary

Lecture Objectives

• Understanding parallel computing technology is necessary to develop AI models using large amounts of data, and make ultra-large AI models. The goal of this lecture is to acquire the ability, to develop ultra-large AI models by parallelizing AI models to quickly learn large amounts of data and efficiently distribute GPU memory.

Course Name

Advanced Data Mining

Summary

Lecture Objectives

• ● This lecture introduces the core techniques in machine learning and data mining, which are important technologies for both data analysis and decision making and supports.● The main contents includes data warehouse, association rules and correlation analysis, classification and prediction, clustering, dimension reduction, Bayesian approach, and so on.

Course Name

Multimodal AI

Summary

Lecture Objectives

• This lecture introduces multimedia data processing techniques based on the latest AI methods. Main contents include multimedia (image/voice/video) data processing, CNN theory and the latest CNN model, image classification, image search, object detection, semantic segmentation, image captioning, image generation (GAN, style transfer, etc.), and data augmentation, transfer learning, multi-modal learning, etc.

Course Name

Application of Big Data and AI for Addressing Social Issues: Focusing on Smart Healthcare and Smart Farming

Summary

Lecture Objectives

• Smart healthcare and smart agriculture are fields that contribute to solving the most important health and food problems for mankind by utilizing big data and advanced artificial intelligence technology. Through this course, students understand smart healthcare and advanced agricultural solutions based on big data, and learn the latest technologies such as data analysis, predictive modeling, and machine learning for problem solving based on real cases. Through this process, they develop core competencies that can contribute to solving various social problems.

Course Name

Generative AI Practical Use

Summary

Lecture Objectives

• The goal of this course is to develop practical skills in utilizing generative AI technology for data analysis and visualization, AI chatbot development, and designing and implementing Arduino-based control systems. Students will understand the principles and real-world applications of generative AI and use this foundation to explore data processing and analysis, natural language processing-based chatbot design, and IoT control system development. Through this, students will enhance their ability to integrate AI technologies with embedded systems and build hands-on problem-solving skills.

Course Name

Advanced Deep Learning with Research Data

Summary

Lecture Objectives

• ● Students acquire the ability to use deep learning technology based on various data such as text, images, and videos used in the field of science and technology.● In particular, we learn the ability to develop deep learning applications by using various deep learning techniques like RNN, transformer, CNN, GAN, and deep reinforcement learning.

Course Name

Advanced Artificial Intelligence

Summary

Lecture Objectives

• ● This lecture introcudes computational mathematics for understanding AI/ML, decision tree, classification, Bayesian, SVM, PCA, matrix factorization, random forest, ensemble, and other core techniques of AI/ML are introduced.● In particular, we study theories, case studies, and trends in AI/ML R＆D based on national science and technology information and research data, and intend to acquire the ability to develop applied AI research/services based on the science and technology data used in practice.