Course Information
Course Overview
This course introduces machine learning and programming fundamentals with a focus on real-world problem-solving in areas such as healthcare and industry. Students will develop practical machine learning applications using tools like Python, Scikit-learn, Keras, and TensorFlow. Advanced topics include deep learning, convolutional neural networks, Transformers, and applications of deep learning to reinforcement learning and control systems.
The course emphasizes project-based and flipped learning, featuring team-based coding projects, English-language presentations, and academic writing. Students will engage in individual or group projects, gaining hands-on experience with AI modeling, algorithmic coding, and addressing real-world engineering challenges.
Use of AI tools—such as ChatGPT, GitHub Copilot, or Cursor—is encouraged to support homework assignments and project development. However, students are fully responsible for the correctness and integrity of their results.
As part of the Mechanical Engineering Project-X, the course encourages problem-solving from a mechanical engineering perspective, aligned with industry and community needs.
Project-X: Real-World AI Research in Action
Project-X is a project-based learning initiative that connects students with real-world challenges sourced directly from industry and healthcare partners. At the start of the semester, we solicit AI-related project proposals from companies, research institutes, and hospitals, reflecting current needs and societal demands.
Students are then presented with a curated list of these projects and asked to indicate their interests and rank preferences. In parallel, students complete a brief survey assessing their programming experience and AI knowledge. Using this information, we thoughtfully form balanced teams—matching students to projects that align with their interests and ensuring a diverse mix of technical skills within each group.
Each project includes two designated mentors:
• A domain mentor, typically from the partner organization, who provides guidance on the application context and domain-specific requirements.
• An ML mentor, often a TA or affiliated researcher, who supports students in applying appropriate machine learning techniques and overcoming technical challenges.
Throughout the semester, students receive hands-on training in AI modeling techniques through a combination of lectures and coding sessions. These skills are directly applied to their chosen project, empowering them to develop and deliver real AI solutions by the end of the course.
Project-X is more than just an academic exercise—it is an opportunity for students to engage with real clients, collaborate as a team, and contribute to solving meaningful problems in engineering, healthcare, and beyond.
Instructor
Prof. Jongeun Choi
Machine Learning and Control Systems Laboratory
School of Mechanical Engineering, Yonsei University
Prof. Jongeun Choi is a faculty member in the School of Mechanical Engineering at Yonsei University and is affiliated with the Department of Artificial Intelligence. He received his Ph.D. in Mechanical Engineering from the University of California, Berkeley, and previously served as a professor at Michigan State University. His research focuses on machine learning, systems and control, symmetry-aware learning, deep reinforcement learning, and Bayesian methods, with applications in robotics, autonomous vehicles, human-robot interaction, and healthcare AI.
Prof. Choi is a Senior Editor for the International Journal of Control, Automation, and Systems, an ASME Fellow, and a former recipient of the NSF CAREER Award. He has received multiple best paper awards and has held leadership roles in vehicle and mobility engineering programs supported by Hyundai Motor Company. In 2023, he was a visiting scholar at UC Berkeley.
Teaching Assistant
Course TA and Programming Support
Teaching Methods
Grading Policy
No midterms, finals, quizzes, or attendance-based grading
Yonsei-ME BK21 Program
As part of the Mechanical Engineering Project-X, the course encourages problem-solving from a mechanical engineering perspective, aligned with industry and community needs. Selected student outcomes may contribute to the 4th stage of the BK21 Program.
A teaching assistant (TA) for this course is supported by the BK21 Program.
KSME
This website was created with support from the Division of Education, Korean Society of Mechanical Engineers (KSME).