Sebastian Raschka's from-scratch video course on building reasoning models
AI researcher Sebastian Raschka has released a new video course focused on building reasoning models from scratch using PyTorch. The course covers inference scaling, reinforcement learning, and distillation to help developers understand how modern LLMs function.
Why it matters
As reasoning models become the standard for LLMs, understanding their underlying architecture is critical for developers and researchers working on advanced AI agents.
Sebastian Raschka, PhD Oct 24, 2026 264 12 27 Share I have written a lot about reasoning models here over the last two years on Ahead of AI, including a recent article on mechanisms to control reasoning effort levels in contemporary LLMs . Reasoning models are still as relevant as ever. In fact, almost all current-generation LLMs today are reasoning models or offer a reasoning mode.
For those who are interested in how reasoning models work, including inference scaling, reinforcement learning, and distillation, I wrote my recent Build Reasoning Model (From Scratch), which implements these from the ground up in PyTorch, which, in my experience, is still the best way to understand and learn how things really work.
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