Course breakdowns, lab deep-dives, AI news with a working-engineer's perspective, and what we've learned training thousands of students on real cloud infrastructure.
Bigger isn't better anymore. Small LLMs fine-tuned for specific tasks are beating GPT-4-class models on real benchmarks, at a fraction of the cost.
Marcus had five years of Node.js experience and zero ML knowledge. Here's the exact ai engineer roadmap he followed, what he built, and what surprised him.
From raw labeled images to a live object detection endpoint in one lab session. Here's exactly how we do it in AI Labs' GPU Training Lab.
Llama, Mistral, Qwen, DeepSeek — four open source LLM families, four very different production tradeoffs. Here's where each one actually belongs in a real stack.
We've run enough cohorts to know: the moment a student hits a CUDA error at 9pm, a recorded video doesn't help. A live instructor does.
Week 12 in our MLOps cohort ends with a live deployment. Here's the exact lab we run to ship an ML model to Cloud Run in under three hours.
QLoRA fits a 13B LLM on one L4 GPU by pairing 4-bit quantization with LoRA adapters. Here's exactly how it works and how to run it yourself.
Autonomous AI agents aren't just demo material anymore. Here are the four patterns we're seeing in real production deployments, and what separates the ones that ship from the ones that stall.
Most ML models die in notebooks. Here's exactly what it takes to get one running on Google Vertex AI Pipelines — from first component to live endpoint.
Embedding models are the unglamorous backbone of every RAG pipeline. Here's how to pick one that won't embarrass you in production.
Most bootcamp portfolios show the same five projects. Here's what hiring managers actually look at — and the AI project ideas that cut through the noise.
Every post on this blog comes out of a real course we teach. Browse the catalog, pick a track, and ship something that holds up in interviews.
Whatever you're trying to figure out, we've probably written about it.
Foundational explainers that don't go stale.
12 posts →Hiring trends, salary data, portfolio advice. From our placement work.
5 posts →Real walkthroughs. Real code. Run it and see for yourself.
4 posts →Why we built each cloud lab and what students actually do in them.
3 posts →New models, papers, releases — and what they actually mean.
2 posts →