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AI Engineering from Scratch: A Structured Path from Theory to Shipping
Rohit's curriculum bridges the gap between LLM fundamentals and actually building products. Worth your time if you're starting from zero.
rohitg00/ai-engineering-from-scratch ↗Most AI courses teach you concepts. This one teaches you to build. The repo walks you through the actual decisions you'll make shipping with LLMs and agents: how to structure prompts, when to use retrieval augmented generation, how to handle failures in production. You get theory just-in-time, paired with concrete code. If you're a solo builder or early-stage team learning to move from "I understand transformers" to "I shipped an AI feature," this cuts the fluff. The curriculum assumes you code already but not that you know AI. Execution quality varies (as with most open curricula), but the structure itself is useful for making a learning plan.
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From LLM fundamentals to shipping: a structured learning path
Rohit's curriculum bridges the theory-to-practice gap for builders starting with AI. Walks through real decisions: prompt structure, RAG, production failures. Strong fit if you're learning applied AI from zero but already code. The territory is well-trodden, so execution matters more than novelty here.
Most AI courses teach concepts. Rohit's teaches you to build. Structured walkthrough from LLM fundamentals to shipping with agents, retrieval systems, and production patterns. Worth mapping if you're at the "I understand theory, now what" stage. https://github.com/rohitg00/ai-engineering-from-scratch
Learning to ship AI features? Rohit's open curriculum bridges the gap between LLM theory and actual product work. Covers prompt engineering, retrieval augmented generation, production patterns, and failure modes. A structured path if you're starting from zero on applied AI. https://github.com/rohitg00/ai-engineering-from-scratch
Just went through rohitg00/ai-engineering-from-scratch and it's the clearest path I've seen for moving from "LLM curious" to "can actually ship". Not a theory dump. It's a structured curriculum that treats building agents and production systems as the real goal, not the bonus round. What lands: → Moves through foundational concepts fast, then straight into applied patterns → Covers the gap most courses leave open: taking a working prototype to something others use → Practical enough that you can follow along with real code, not just read about it This is ICP for builders who want the connective tissue between "how transformers work" and "how to actually deploy a system". If you're starting from zero on production LLM work, the structure matters more than the novelty here. Go build something. https://github.com/rohitg00/ai-engineering-from-scratch
been reading through rohitg00/ai-engineering-from-scratch. it's rare to find a curriculum that doesn't stop at "here's how attention works" and actually takes you through shipping. the structure: theory, then applied patterns, then real deployment concerns. not groundbreaking conceptually, but the execution bridges a real gap for builders. if you're learning LLMs to build something (not just learn), this saves months. https://github.com/rohitg00/ai-engineering-from-scratch