AI융합학과 (AI Convergence Division)
외국인 전담학과, English Track
For experts to lead the AI era and the next generation – The ‘AI Convergence Division’ offers a curriculum that uses AI as a tool to solve complex challenges across multiple domains.
‘The AI Convergence Division’ is not just a hub for cutting-edge technologies; it’s a playground for those who aspire to shape the future through intelligent systems and entrepreneurship.
We Have 2 Tracks
ㆍAI Robotics: Designing a program that encompasses both artificial intelligence (AI) and robotics
ㆍAI Business Management: Integrating artificial intelligence (AI) technologies into traditional business management principles.
2 Years Course
For associate bachelor degree, 2 Years Course:
1. Foundations of AI & Digital Literacy
2. Core Technologies & Applied Learning
More 2 Years Course
For bachelor degree, More 2 Years Course:
3. Industry-Oriented Advanced Studies
4. Capstone Design & Global Readiness
Core Areas of Study
‧AI Robotics track
1. Foundations of AI: Introduction to AI concepts, algorithms, and methodologies, including machine learning, deep learning, reinforcement learning, and natural language processing.
2. Foundations of Robotics: Basic principles of robotics, including kinematics, dynamics, sensors, actuators, and control systems.
3. Robot Perception and Sensing: Techniques for robot perception, sensor fusion, localization, mapping, object recognition, and scene understanding.
4. Robot Control and Planning: Algorithms for motion planning, trajectory generation, path optimization, and feedback control in robotic systems.
5. Autonomous Systems: Concepts and methods for developing autonomous robots and intelligent systems capable of decision-making and adaptation in dynamic environments.
6. Applications of AI and Robotics: Case studies and projects that apply AI and robotics technologies to address real-world challenges in manufacturing, healthcare, logistics, agriculture, space exploration, and other domains.
‧AI Business Management track
1. Foundations of AI: Introduction to AI concepts, algorithms, and methodologies, including machine learning, deep learning, natural language processing, and computer vision.
2. Business Strategy and AI: Examining how AI can be used to develop and implement business strategies, optimize operations, and create new revenue streams.
3. AI-enabled Marketing and Customer Analytics: Utilizing AI techniques for customer segmentation, personalized marketing, sentiment analysis, and customer relationship management.
4. AI in Finance and Investment: Applying AI algorithms for financial forecasting, risk management, algorithmic trading, and portfolio optimization.
5. AI driven Operations Management: Using AI-powered solutions for supply chain optimization, inventory management, production planning, and logistics.
6. AI for Business Intelligence: Harnessing AI technologies to extract insights from big data, perform predictive analytics, and support strategic decision-making.