Sebastian Raschka releases from‑scratch video course on reasoning models
inference reasoning
| Source: HN | Original article
Sebastian Raschka launches a video course that teaches how to build reasoning models from scratch.
Sebastian Raschka, a veteran LLM research engineer, has launched a free, eight‑part video course that walks Python and PyTorch developers through the construction of reasoning‑oriented language models from the ground up. The series, posted on Raschka’s personal site and mirrored on YouTube, covers core topics such as inference scaling, reinforcement learning, and model distillation, and provides a complete codebase that implements each step in PyTorch. Accompanying the videos are chapter‑level notes, reusable code resources and a set of articles that explain how conventional large language models differ from newer reasoning‑focused agents.
The offering matters because it demystifies a segment of AI that has largely remained behind the curtain of corporate research labs. By exposing the engineering pipeline—starting with a pre‑trained LLM, exposing the mechanics of text generation, and then layering evaluation tools and reasoning capabilities—Raschka gives independent researchers and smaller teams a practical pathway to experiment with next‑generation models without needing proprietary infrastructure. The course’s emphasis on “from‑scratch” implementation also aligns with recent industry cautions about training on live internet data, underscoring a shift toward more controlled, reproducible development practices.
Watch for community uptake in the coming weeks: developers are likely to fork the repository, adapt the modules for domain‑specific tasks, and share benchmark results. Raschka’s reputation and the early endorsement from a Google AI researcher suggest the material could become a reference point for open‑source reasoning‑model projects, potentially influencing curricula in Nordic universities and fueling local startup prototypes that aim to embed advanced reasoning into their products.
Sources
Back to AIPULSEN