AI3001: Advanced Deep Learning
AI3001: Advanced Deep Learning
Efficient Multimodal Intelligence Laboratory
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Instructors: 최성하
Teaching Assistant: 최용빈
SW Mentor: 안성재
This course aims to help students understand the fundamentals of modern AI models, from Attention and Transformers to LLMs, multimodal models, efficient training techniques, and generative models. Through simple hands-on assignments using PyTorch and Hugging Face, students will also develop an intuitive and practical understanding of these concepts.
Attendance will be verified via Info21 using a code provided in class.
Environment Setup: Please complete the Docker installation before the first assignment
The course will primarily use lecture slides and selected reference materials, which may include:
CS224N: Natural Language Processing with Deep Learning (https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1246)
CS231N: Deep Learning for Computer Vision (https://cs231n.stanford.edu/2025)
CME295: Transformers & Large Language Models (https://cme295.stanford.edu/)