6 Weeks
·Cohort-based Course
Learn the key AI engineering patterns by building an app that extracts insights from unstructured text. Practical AI insights for developers
This course is popular
4 people enrolled last week.
6 Weeks
·Cohort-based Course
Learn the key AI engineering patterns by building an app that extracts insights from unstructured text. Practical AI insights for developers
This course is popular
4 people enrolled last week.
Taught devs, founders, and managers at
Course overview
You're going to create an "Insights Extraction AI App" ("Unstructured Text Data" to "Structured Insights") using a modern stack of tools and AI engineering patterns
An end-to-end deployed (live on the web) application that converts unstructured data (podcast, meeting notes, customer feedback, essays, etc.) and outputs structured insights (tweets, product descriptions, summaries, etc.).
The goal is to build & learn a flexible application structure so you can extend to your use case.
Example applications you'll be able to extend this course's code to: Meeting "Next Steps" extractor, Podcast Summarizer, Customer Survey Trends Extractor, Extract class lessons from lectures, Data stream classifier, Custom apps with your own data
AI Engineering Patterns we'll cover:
* Prompting - The basic 3 step pattern for writing development prompts + optimizers, structured outputs
* Observability - To manage costs, tracing and debugging
* Retrieval/Chains - Adding more context to your LLMs and connecting multiple LLM calls together for a unified outcome
* Model Choice - Tribal knowledge about when to pick certain models over another (spoiler: it depends on your use case)
* Evals - The new style of unit tests for your LLM apps
* Mindset - You'll learn how to approach novel problems with AI
We promise three outcomes with this course:
* You’ll launch an AI-powered app designed to teach you the foundations to build your own tools
* You’ll surround yourself with a new group of friends: other builders who are as passionate as you (and hold you accountable)
* You’ll 2x your likelihood to ship by experiencing first-hand the greatest trait a builder can have: a bias for action
You'll get experience building with a modern AI powered development stack:
* Cursor - Write code, but with ChatGPT by your side
* v0 - Build user interfaces with words, not code
* LLMs - Outsource intelligence to Large Language Models APIs like OpenAI/Anthropic
* LangChain/LangSmith - Orchestrate and observe your LLM calls, ensuring your costs don't run out of control
* Railway/Vercel - Deploy your apps
* Supabase - Simple postgres database
* Zapier - Simple ways to quickly integrate your application with other tools
* Anthropic Artifacts - For prototyping mini applications
"The best way to get good at something is usually to just practice actually doing the thing in question. A lot of very capable people outsmart themselves with complex plans that involve working a lot on fake prerequisites." - Sam Altman 10/27/2024
It’s no longer skill level that's holding you back, it’s just your desire to take a step forward.
Along the journey, you’ll have access to mentors, successful builders that have built apps, a network of like-minded people, creative workshops, and 1:1 sessions.
This program is a fast-paced, highly engaging program, but you don’t need to take time off work to participate. We’ve designed the program to be as flexible as possible for those who work full-time or have busy schedules.
With that said, we encourage you to commit to at least 4-5 hours of your spare time each week, for deep work, feedback groups, and live sessions.
In addition to the course material, this cohort includes:
* Code Templates - All materials shown in class will be available for download so you can continue to quickly build after the class
* Slack - A channel for you to ask questions, connect with other builders, and get support on your projects
* Guests - Each week we'll feature an expert from the industry to talk about AI Engineering
This course is not:
* Learn to be a programmer from scratch
* Learn the absolute basics
* Learn how to fine tune LLMs
On the traditional SWE side, we will build our backend with Python and Postgres, frontend with Next.js, and deployed on Railway. Though this course is taught in python, you have the flexibility to bring whatever tool stack you're comfortable with.
Who you are
* You have a intermediate level understanding of Python + Javascript (React is a plus)
* You're not afraid to roll up your sleeves and learn new technology
* You value shipping something quick
* You want to build AI-powered products
* You're ready to break a big problem down into shippable chunks
01
Scrappy Developers. You're a hands-on builder ready to turn your skills into real AI applications, even if development isn't your day job
02
Technical Leaders. CTOs and technical managers who are struggling to elevate the AI conversations with their teams
03
Experienced Developers. Software Engineers who want to build AI products but haven't dove into an AI focused tool stack yet
Playbook of best practices for 5 areas of LLM development
Become proficient in prompting, observability, chaining, model choice, structured outputs and scaling apps
A deployed "Insight Extraction" app live on the web
You'll build your own tool which will start saving you time from Day 1. We'll walk through the steps of deploying your application on a custom domain (Ex: YourCoolAppYouBuilt.com)
A survey of modern AI tools that will speed boost your workflow
You'll gain hands-on experience with Cursor, v0, LLMs (OpenAI, Anthropic, Google), LangChain & LangSmith, Railway/Vercel, Supabase, Zapier, and Anthropic's Artifacts
Instructions to scale your LLM apps
We will run through step by step instructions on how to reduce the cost and latency of your LLM apps while maintaining (or even increasing) performance. This is critical to keep your LLM costs under control
13 interactive live sessions
Lifetime access to course materials
19 in-depth lessons
Direct access to instructor
1 projects to apply learning
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Build With LLMs: AI Engineering Patterns for Scrappy Developers
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Harrison Chase
Wade Foster
Dharmesh Shah
Sanyam Bhutani
Founder @ Leverage, AI Educator
Greg Kamradt, AI Product & Education Leader @ Leverage, has helped over +100K developers build AI applications from companies like Google, Zillow, Meta, Nvidia, and Microsoft. Currently, he is CEO of Leverage, an AI Product & Education Studio. Previously he was Director of Growth at Salesforce.
Greg authored the original "Needle In A Haystack" analysis, testing the long-context utilization of LLMs. Greg also co-leads ARC Prize, $1M competition to beat the #1 AGI benchmark, ARC-AGI.
With over 51K subscribers on YouTube, Greg is an active leader & voice in building AI applications.
Join an upcoming cohort
Cohort 1
$725
Dates
Payment Deadline
4-6 hours per week
Saturdays
10:00am - 11:00am PT
If your events are recurring and at the same time, it might be easiest to use a single line item to communicate your course schedule to students
Jan 6, 2024
We'll kick off the course in the new year
Weekly projects
3 hours per week
Each week will consistent of live instruction, video overviews, and "homework" (the fun kind) through practicing to build.
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Sign up to be the first to know about course updates.
Join an upcoming cohort
Cohort 1
$725
Dates
Payment Deadline