Master the LLM Stack in 60+ hours — learn, code, ship, and certify
Author: Towards AI Editorial Team
Originally published on Towards AI.
Over the past two years, we’ve helped teams design and deploy real-world LLM systems — RAG pipelines, copilots that actually reduce load, PoCs that became products, and cut down hallucinations.
One year ago, we decided to put everything we knew about building architectures around LLMs — the stack, the mistakes, the gotchas, the strategies — into a single guide:
Building LLMs for Production — “the most comprehensive textbook to date on building LLM applications,” as Jerry Liuput it.
The response was amazing. People read it. People built with it. People shared it.
But a few months in, our DMs started filling up:
“Has the book been updated?”
“Does it cover the latest models like o3 or Gemini 2.5?”
“Can I useinstead?”
“How do I choose the right model for my use case?”
“What if I want to dothat isn’t in the book?”
Fair. The landscape’s shifting fast.
Inference got scaled. SLMs showed up. Context windows stretched. Costs dropped. Everything moved.
If AI has taught us anything, it’s to think AI-first — not just to keep up, but to build in ways that scale.
So instead of answering each DM, we took a step back. And we decided to build something that answers all of it, now and as things evolve.
The result?
From Beginner to Advanced LLM Developer
A 60+ hour, hands-on course that takes you from “I can prompt ChatGPT” → to deploying a production-grade RAG system with a real front end.
But we didn’t just pack it with knowledge — we designed it to evolve with the field.
Here’s what you walk away with:
A repeatable pipeline that adapts with tools, not trends
A deep instinct for how to think like an AI engineer
Lifetime access and weekly updates as the ecosystem changes
A private Slack for graduates + a 70,000+ builder community on Discord
Because staying current isn’t enough — you also need confidence that what you ship today still holds tomorrow.
That’s why we’re now running monthly live cohorts — so you stay sharp, supported, and up to date.
The next cohort kicks off June 1 with a live welcome call with our CEO.
Launch price:— zero risk thanks to a 30-day money-back guarantee.
Join the course here
The results speak for themselves:
“The course greatly expanded my knowledge of building and assessing RAG pipelines.” — Eoin McGrath
“Best course out there to become an AI engineer. Planning to build my own startup based on the learnings.” — Abhijit L.
“From zero to hero as an LLM Developer — a clear path to build LLM applications that can change your career.” — Luca Tanieli
Even industry voices you know have shared support:
“A resource I’ll return to again and again, no matter how fast the AI landscape shifts.” — Tina Huang, Lonely Octopus
This course is for you:
You know Python but haven’t taken an LLM past the notebook.
If you’re frustrated by shallow tutorials and fragmented docs…
If you want to build things that work, not just read about them…
If you’re ready to take LLMs seriously and want a proven structure…
There’s a roadmap. And it’s working.
The next cohort starts June 1st. As soon as you join, you get full access to all course material — no need to wait for the live kickoff. You can start building right away.
What You’ll Learn:
LLM Basics & Prompt Mastery
Transformers, tokenization, and prompting that actually reduces hallucinations
Retrieval-Augmented GenerationChunking, embedding models, re-ranking, query rewriting, eval, and feedback loops
Fine-Tuning
LoRA, adapters, and domain-specific models that actually perform
Tool & API Integration
Function calling, external tools, and chained agent workflows
Deployment & Cost Control
Gradio, Streamlit, latency fixes, caching, logging, monitoring, cost tracking
Capstone Project & Certification
Build and ship your own LLM app — get feedback, and leave with a portfolio-ready build
If you’re thinking, “This sounds great, but what if it’s not for me?” — we get it. That’s why the course comes with a 30-day, no-questions-asked money-back guarantee. Try it. Dive into the material. If it doesn’t meet your expectations, we’ll refund you in full.
Secure your spot for the June 1st cohort
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
#master #llm #stack #hours #learn
Master the LLM Stack in 60+ hours — learn, code, ship, and certify
Author: Towards AI Editorial Team
Originally published on Towards AI.
Over the past two years, we’ve helped teams design and deploy real-world LLM systems — RAG pipelines, copilots that actually reduce load, PoCs that became products, and cut down hallucinations.
One year ago, we decided to put everything we knew about building architectures around LLMs — the stack, the mistakes, the gotchas, the strategies — into a single guide:
Building LLMs for Production — “the most comprehensive textbook to date on building LLM applications,” as Jerry Liuput it.
The response was amazing. People read it. People built with it. People shared it.
But a few months in, our DMs started filling up:
“Has the book been updated?”
“Does it cover the latest models like o3 or Gemini 2.5?”
“Can I useinstead?”
“How do I choose the right model for my use case?”
“What if I want to dothat isn’t in the book?”
Fair. The landscape’s shifting fast.
Inference got scaled. SLMs showed up. Context windows stretched. Costs dropped. Everything moved.
If AI has taught us anything, it’s to think AI-first — not just to keep up, but to build in ways that scale.
So instead of answering each DM, we took a step back. And we decided to build something that answers all of it, now and as things evolve.
The result?
From Beginner to Advanced LLM Developer
A 60+ hour, hands-on course that takes you from “I can prompt ChatGPT” → to deploying a production-grade RAG system with a real front end.
But we didn’t just pack it with knowledge — we designed it to evolve with the field.
Here’s what you walk away with:
✅ A repeatable pipeline that adapts with tools, not trends
✅ A deep instinct for how to think like an AI engineer
✅ Lifetime access and weekly updates as the ecosystem changes
✅ A private Slack for graduates + a 70,000+ builder community on Discord
Because staying current isn’t enough — you also need confidence that what you ship today still holds tomorrow.
That’s why we’re now running monthly live cohorts — so you stay sharp, supported, and up to date.
The next cohort kicks off June 1 with a live welcome call with our CEO.
Launch price:— zero risk thanks to a 30-day money-back guarantee.
👉 Join the course here
The results speak for themselves:
“The course greatly expanded my knowledge of building and assessing RAG pipelines.” — Eoin McGrath
“Best course out there to become an AI engineer. Planning to build my own startup based on the learnings.” — Abhijit L.
“From zero to hero as an LLM Developer — a clear path to build LLM applications that can change your career.” — Luca Tanieli
Even industry voices you know have shared support:
“A resource I’ll return to again and again, no matter how fast the AI landscape shifts.” — Tina Huang, Lonely Octopus
This course is for you:
You know Python but haven’t taken an LLM past the notebook.
If you’re frustrated by shallow tutorials and fragmented docs…
If you want to build things that work, not just read about them…
If you’re ready to take LLMs seriously and want a proven structure…
There’s a roadmap. And it’s working.
The next cohort starts June 1st. As soon as you join, you get full access to all course material — no need to wait for the live kickoff. You can start building right away.
What You’ll Learn:
🧠 LLM Basics & Prompt Mastery
Transformers, tokenization, and prompting that actually reduces hallucinations
🔍 Retrieval-Augmented GenerationChunking, embedding models, re-ranking, query rewriting, eval, and feedback loops
🎨 Fine-Tuning
LoRA, adapters, and domain-specific models that actually perform
🤖 Tool & API Integration
Function calling, external tools, and chained agent workflows
🚀 Deployment & Cost Control
Gradio, Streamlit, latency fixes, caching, logging, monitoring, cost tracking
🏆 Capstone Project & Certification
Build and ship your own LLM app — get feedback, and leave with a portfolio-ready build
If you’re thinking, “This sounds great, but what if it’s not for me?” — we get it. That’s why the course comes with a 30-day, no-questions-asked money-back guarantee. Try it. Dive into the material. If it doesn’t meet your expectations, we’ll refund you in full.
👉 Secure your spot for the June 1st cohort
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
#master #llm #stack #hours #learn
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