LLMO4

Cohort 1 has been open-sourced  @ bit.ly/llmops1

LLM Ops has expanded into The AI Engineering Bootcamp @ bit.ly/AIEbootcamp

Dr. Greg Loughnane

Founder & CEO @ AI Makerspace

Chris "The LLM Wizard 🪄" Alexiuk 

Co-Founder & CTO @ AI Makerspace

LLM Ops - Large Language Models in Production

Future-proof your career with AI engineering. Design, assemble, and operate production LLM applications with industry-standard tools. Data science and ML skills that were relevant just a few years ago are being outpaced by AI. It is now possible to build what used to take months in a single day! This course is designed to help you think at the right level of abstraction about AI, and to write code that will help you prototype and ship production LLM applications at the leading edge.

Become the AI Engineer that every company needs

Advanced developers with an understanding of fundamental ML concepts and the product development process

Experienced data scientists or machine learning engineers who want to build production LLM applications

Software engineers who want to get up to speed on Generative AI and explore new career opportunities

Who is this course for

What you’ll get out of this course

Engineer LLM apps from scratch with Python and using LLM Ops frameworks including LangChain and LlamaIndex

Build, deploy, evaluate, and improve production Retrieval Augmented Generation (RAG) Question Answering systems

Master key LLM product development techniques like prompt engineering for retrieval, caching, and versioning

Learn to leverage Agents across LLM Ops frameworks using Reasoning-Action (ReAct) logic

Work with other talented builders to bring your LLM project or startup idea to life

<ul><li>LLM Ops&nbsp;vs. MLOps</li><li>Build your first LLM Application with Chainlit and Hugging Face</li><li>Build a Retrieval Augmented Generation (RAG) 101 with GPT-4 Turbo and OpenAI's API</li><li>LLMOps Visibility with Weights and Biases</li></ul>

🧑‍💻 Building LLM Applications in Pure Python

<ul><li>Intro to LangChain and LangServe</li><li>Prompt and embedding caching in RAG systems</li><li>Build a RAG with LangChain, OpenAI, and Pinecone</li><li>Evaluate retrieval and generation metrics for metric-driven development with RAGAS</li><li>Improve RAG systems with advanced retrieval</li></ul>

🔗 LangChain Powered RAG and Advanced Retrieval

<ul><li>Deploy a Mistral-7B-powered RAG system built with LangChain, FAISS to production via Amazon SageMaker</li><li>Intro to LlamaIndex</li><li>Build a RAG with LlamaIndex &amp; Unstructured.io, GPT-4 turbo, and Chroma that combines retrieval of tabular and language data</li><li>Index versioning with Weights and Biases</li></ul>

Open-Source Production RAG with 🦙 LlamaIndex and  🌬️ Mistral

<ul><li>All things ReAct agents, function calling and external tools!</li><li>LangChain vs. LlamaIndex</li><li>LangSmith and the evolving LLM Ops landscape</li><li>LLM Ops Hack Week!</li><li>Demo Day!</li><li>Graduation!</li></ul> For more details check out the resource below👇!

🕴️Agentic Systems, 🧑‍💻 Hackathon, and 🧑‍🏫 Demo Day!

Course syllabus (download the detailed schedule for the entire syllabus!)

LLM Application Learning Outcomes

Prerequisite

Tools include VS Code, UNIX terminal, Jupyter Notebooks, and Conda package management. 🔗 Resource Links: <a href="https://www.youtube.com/live/4pkzY95Otm4?feature=share" rel="noopener noreferrer" target="_blank">Video</a>, <a href="https://github.com/AI-Maker-Space/Interactive-Dev-Environment-for-LLM-Development" rel="noopener noreferrer" target="_blank">Code</a>

Be able to leverage a standard Interactive Development Environment (IDE) for building LLM software

🔗 gpt-3.5-turbo, gpt-4 links: <a href="https://www.youtube.com/live/pRbbZcL0NMI?si=4Gk8xRoc_vR9XfMa" rel="noopener noreferrer" target="_blank">Video</a>, <a href="https://colab.research.google.com/drive/1mOzbgf4a2SP5qQj33ZxTz2a01-5eXqk2?usp=sharing" rel="noopener noreferrer" target="_blank">Code</a>🔗 gpt-4-turbo, DALL·E 3 links: <a href="https://www.youtube.com/live/rJm3nBzCmCY?si=VQdML4PkHbgdklLk" rel="noopener noreferrer" target="_blank">Video</a>, <a href="https://github.com/AI-Maker-Space/GPT4AppWithDALLE3" rel="noopener noreferrer" target="_blank">Code</a>

Be able to programmatically access Open AI API as a developer

Associate Manager, Digital, Analytics, and Technology

What people are saying

Meet your instructors

<ul><li>Nov 28th, 30th</li><li>Dec 5th, Dec 7th</li><li>Dec 12th, Dec 14th</li><li>Dec 19th, Dec 21st</li></ul> * All sessions will be recorded for your viewing pleasure!

Class!

Each class period, we will get hands-on with Python coding homework!

Programming Assignments

<ul><li>Monday: Team formation, project ideation, storytelling workshop, system diagram presentation</li><li>Wednesday: Build 🏗️, ship 🚢, and share 🚀 a RAG system with at least the following components: caching, evaluation, visibility&nbsp;</li></ul>

LLM Ops Hack Week

<ul><li>Open to the pubic - Friends, family, coworkers and bosses welcome!</li></ul>

LLM Ops Demo Day

<ul><li>Greg Loughnane: Mondays @ 8 AM PT</li><li>Chris Alexiuk: Fridays @ 3 PM PT</li></ul>

Office Hours

Course schedule

We're here to teach concepts plus code. Never one or the other.

Get hands-on with code, every class

Grow your network. Build together. Feel the difference that expert facilitation makes.

Pair programming made fun and easy

Join a community of doers, aimed in the same career direction as you are.

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