@FinanceYF5: Setting aside the story of a friend landing a 750k salary with this, the video itself is pure substance—a 3-hour hands-on walkthrough of building an LLM from scratch. It covers five stages: LLM basics, Transformer architecture, training process, model modernization, and scaling. Code is fully visible, typed out as explained. If you want to understand how ChatGP…
Summary
A 3-hour hands-on walkthrough of building an LLM from scratch, covering five stages: LLM basics, Transformer architecture, training, model modernization, and scaling, with code visible throughout.
View Cached Full Text
Cached at: 07/10/26, 12:11 PM
Putting aside the story about a friend landing a 750k salary by using this, the video itself is packed with solid substance — a 3-hour live recording of building an LLM from scratch.
It covers five stages: LLM basics, Transformer architecture, training process, model modernization, and scaling. The code is fully visible throughout, with live coding and explanations.
Want to understand how ChatGPT and Claude are built? 👇 https://t.co/F8tQUqyRM5
Similar Articles
@AYi_AInotes: Fellow developers working on LLM production deployment, check out Andrew Ng's new course. The free version gives you access to all videos and base code. This course is not another rerun of the 'Attention is All You Need' math derivation, nor another set of mystical prompt-tuning tricks, nor yet another toy...
Andrew Ng has launched a new course on LLM production deployment. The free version provides access to all videos and base code. The course dives deep into LLM internals, inference optimization (such as quantization, KV Cache, Flash Attention, speculative decoding), and hardware-aware optimization. Taught by AMD's VP of Engineering, it aims to help developers transform Transformer from an academic concept into a debuggable, optimizable engineering tool.
@vintcessun: 3 courses updated in 3 days: Day00 Learning Map, Day01 Transformer Overview, Day02 Input Layer. One course each morning, with illustrations, tables, formulas, and checklists. The greatest value of this path is letting beginners build understanding starting from the input layer, rather than diving directly into papers. What you learn is—understanding tok…
Published a GitHub repository with an LLM learning path for beginners, covering course content from Transformer basics to LLM techniques, with one course updated daily.
@JustinAngel: https://x.com/JustinAngel/status/2069482255312195980
Release of free workshop recordings and materials (23 videos, 250 slides, 50 exercises) for building your own LLM from fundamentals to transformer architecture, with no math or ML prerequisites.
@huoshan007: Came across this today, it's actually insane. Someone just released an entire 1-hour Claude course for free—no fluff, but actually how to build stuff with Claude, automate workflows, and even make money with it. In short, skip one episode of your show, spend this hour, and by tomorrow you might have a marketable skill.
Someone has released a full 1-hour Claude course for free, covering how to build applications, automate workflows, and monetize using Claude.
@Stephen4171127: Recently discovered an open-source tool called Claude-real-video, which directly hits the deadlock of current LLM video analysis. Previously, the entire industry was fiercely competing to 'natively bake video capabilities into large models,' which is equivalent to every company having to build a phone with a screen from scratch — either wait for big players to slowly roll out features, or burn money training small models. Ordinary developers simply can't keep up…
Introducing the open-source tool claude-real-video, which uses scene change detection and audio transcription to allow any LLM to analyze videos locally, solving the pain points of fixed-frame sampling and cloud uploads.