The iAI KAIST page shares deep learning materials that visitors are permitted to use, modify, and distribute.

iailab.kaist.ac.kr/teaching/deep-learning
IAILab homepage screenshot

About IAILab

The iAI KAIST page provides deep learning lecture materials that are openly available to everyone. Topics include Python basics, optimization, machine learning, neural networks, CNNs, transformers, large language models, diffusion models, physics-informed AI, and deep reinforcement learning.

Materials are listed with Colab notebooks, PDF slides, PowerPoint files, problem sets, and solutions, alongside YouTube videos in Korean and English. Visitors are permitted to use, modify, and distribute the materials, with no credit required.

Key features

  • Deep learning topics with Colab notebooks, slides, and problem sets
  • YouTube lectures available in Korean and English
  • Coverage of CNNs, GANs, diffusion models, and transformers
  • Physics-informed neural networks and neural operator materials
  • Deep reinforcement learning section with labs and slides
  • Problem sets with solutions for self-study
Best for: Students and instructors who want reusable deep learning materials for study or teaching.
Good for
  • Materials can be used, modified, and distributed with no credit required
  • Includes Colab notebooks, slides, PowerPoints, problem sets, and solutions
  • Lecture videos are linked in both Korean and English
Watch out for
  • Site states it uses Google cookies and shares usage information with Google

IAILab at a glance

Type
Website
Pricing
Not confirmed. Check the site
Platforms
Web
Open source
Not stated
Language
English
Good for
Students
Last checked
Oct 5, 2026 · Online when checked
Listed
Oct 5, 2026

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IAILab FAQ

Can I use these materials in my teaching?
Yes. The site states instructors may use, modify, and distribute the materials, with no credit required.
Are the lectures available in English?
Yes. The deep learning section links to YouTube videos in Korean and in English.
What types of files are included?
The topic tables list Colab notebooks, PDF slides, PowerPoint files, problem sets, and solutions.
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