【Enrollment Now Open】College of Engineering AI Course, Fall 2026

Deep Learning Project Design (EG5015)

I. Course Highlights

Want to turn AI concepts into fully functioning projects?

Deep Learning Project Design guides students through the entire process of developing a deep learning project using PyTorch—from dataset preparation, model construction, training, and validation to model evaluation, data augmentation, and performance improvement.

The course covers Python and PyTorch review, tensor operations, neural networks, image learning, convolutional neural networks (CNNs), and real-world image project development. Students will also complete a final project, transforming what they have learned into a practical portfolio piece that can be demonstrated and further developed.

This course is especially suitable for students who already have a basic understanding of AI and deep learning, as well as fundamental programming skills in C++ and Python. Through lectures, hands-on practice, experiments, and individual guidance, students will not only learn essential deep learning techniques but also develop the ability to define problems, process data, design models, analyze results, and independently complete AI projects.

From understanding models to building them, and from classroom exercises to a completed project, Deep Learning Project Design will help you establish a stronger foundation for academic research, engineering applications, and future AI development.

II. Course Information

• Course Title: Deep Learning Project Design
• Course Number: EG5015
• Instructor: Prof. Chao-Yang Liao
• Time and Location: Fridays, 09:00–11:50 | Classroom E2-308
• Enrollment Capacity: 10 students

Eligible Students: Junior and senior undergraduate students, master’s students, and doctoral students from departments and institutes within the College of Engineering, excluding the Department of Mechanical Engineering