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Become an AI Engineer in the world’s leading community for people who want to build, ship, and share production LLM applications 🏗️🚢🚀.
Dr. Greg and The Wiz Maven – The AI Engineering Bootcamp (2025)
Course overview
Prototype agent apps and get them into Production. Ship fast and keep data safe.
🧑💻 ON CODING AS AN AI ENGINEER
– Do you code every day?
– If not, are you committed to coding every day as an AI Engineer?
If the answer to both of these questions is “No,” this class is not for you.
💼 ON LEADING AI ENGINEERING TEAMS
– Do you manage a team of people that writes code every day?
If “Yes,” this class might be for them.
——
**KEY CURRICULUM UPDATES FOR COHORT 8**
🛠️ Context Engineering, Level 0 (Prompting), Level 1 (RAG), Level 3 (Agents), and Advanced Context Engineering!
🤯 Why LLMs Hallucinate (Sept 2025)
🧩 The Limitations of Dense Vector Retrieval (Sept 2025)
🌐 Open-source models & embeddings introduced much earlier, both remotely via TogetherAI and locally via ollama
⚡ LangChain v1.0 alpha
🤖 Deep Agents
📊 Evaluating the Evaluators (Aug 2025) & In Defense of Evals (Sep 2025)
🏆 Demo Day Semi-Final Competition Round
A brand new primary cohort use case that builds on itself and runs throughout the cohort: Deep Research from Scratch
**KEY CURRICULUM UPDATES FOR COHORT 7**
🟢 [New Additions]
– Context Engineering from first principles
– A primary cohort use case that builds on itself and runs throughout the cohort
– Expansion of Model Context Protocol (MCP) content
– Using Agent2Agent (A2A) Protocol to build and run two agents, one w/ MCP server and one to mimic a human using our agent
– Dedicated Guardrails session, from best-practices to implementation
🔴 [Deprecated]
– Explicit teaching of code and coding agents (in favor of a more implicit approach of using Claude Code regularly)
– Computer Use agents (in favor of A2A and operating an Agent in production)
– Contextual Retrieval
– Hugging Face smol agents
——
OUR COMMUNITY
🏗️ 🚢🚀 AI Makerspace is on a mission to create the world’s leading community for people who want to build, ship, and share production LLM applications.
Welcome! We invite you to join our close-knit AI Makerspace community on YouTube (learn live weekly with us for free at 10 AM PT on Wednesdays!) or Discord to start building, shipping, and sharing with us today!
https://aimakerspace.io/
OUR COURSE
The AIE Bootcamp is truly a bootcamp. It’s hard. It’s a grind. But it will transform you! It will get you comfortable thriving at “The LLM Edge” and beyond. Our students don’t just learn; they transform!
Plus, every cohort culminates in a live Demo Day experience! Many of our graduates have launched entirely new startups based on their demo day presentations!
To hear our student’s stories and for a quick glance at all the tools you’ll master, check out the following link now!
https://aimakerspace.io/the-ai-engineering-bootcamp/
OUR ETHOS
Build 🏗️, Ship 🚢, Share 🚀!
This is the secret to success in a 21st-century workforce, and you will live this every class, every week of the cohort!
🧑🤝🧑 Specifically, you will get hands-on experience building and sharing complex LLM and agentic applications weekly, receiving constant feedback during live sessions and through your homework submissions via instructors, peer supporters, and your fellow cohort members.
🙋 WHAT ARE THE PREREQUISITES
You must be familiar with Python programming, prompt engineering, and data science. Learn more about prerequisites here: https://bit.ly/aie7-prereqs
🙋 How will I know if it’s right for me?
If you’re unsure if this course be a fit for you, you’ll find tons of resources on this page to help you decide, including:
📜 Curriculum & Detailed Schedule: https://bit.ly/aie7-curr
🤩 Demo Day Videos (from cohort 5): https://bit.ly/aie5-demos
🎤 Student Interview Videos: https://aimakerspace.io/category/transformations/
Here are a few long-form pieces of writing about the student experience:
– Richard Gower, Cohort 3: https://bit.ly/aie-cohort-3-reflections
– Ches Roldan’s “20 Tips to Survive AI Makerspace’s AI Engineering Bootcamp (as a non-technical person)”: https://bit.ly/aie-20tips
💰 How much do the tools cost?
Don’t worry! This course is for the GPU-poor among us! This course adapts to industry-standard open-source software and compute hardware and is cloud platform agnostic. We strive to keep your additional costs low (below ~$100 total). Check Q&A for more info!**
WHO HAS TAKEN THIS COURSE
Since its launch in January 2024, over 250 people have taken the course! The most successful participants have been Software Engineers and Developers or Data Scientists and Machine Learning/AI Specialists, indicating a focus on analytics, modeling, and artificial intelligence.
Here is a list of companies whose employees have already taken the course:
Google, Meta, Microsoft, Amazon, Samsung, Salesforce, IBM, Oracle, Bloomberg, Deloitte, Atlassian, SAP, Infosys, ServiceNow, Shopify, NetApp, Autodesk, Jio Platforms, JP Morgan Chase (JPMC), Walmart, Chevron, Expedia, NTT Data, Ernst & Young, Fannie Mae, National Grid, State Farm, USAA, BMO, TD Bank, Mercer, Kiewit, BP, CVS, Safran, Appian
The most important thing for anyone taking the course is to take it seriously. This advanced course requires commitment, debugging, resilience, and tenacity. These personal attributes matter much more than your current company or job title.
Whether you’re coming from a software engineering or data science background, to be a world-class AI Engineer, you’ll need to know both. This class will teach you the lego blocks of building production-grade LLM applications software as an AI-Assisted Developer. This is where your journey begins!
Top 10 direct quotes from Cohort 5
“One of the best lessons I’ve ever had. The instructor’s level of expertise is high and his communication is extremely easy to understand. I have grasped all the concepts.”
“This session was pure gold, seeing actual applications, really nice!”
“I am having lots of fun and learning. LOVE THE ENERGY! Let’s go.”
“The breakout rooms are absolutely fantastic. Peer Supporters are bae.”
“The breakout rooms are just so good – easily sets it apart from 90% of other courses out there.”
“It was a great session today. Super helpful and getting clearer. Amazing job everyone. Love this!!!!”
“I have deployed and built a number of applications right from the first sessions of the course. Knowledge also helps me in self-study and research.”
“This class was worth every dollar, thank you guys!”
“Thank you for an amazing ride! <3”
“I complained last time about the breakout rooms not being long enough and the lectures being too long. This time I think the ratio was GLORIOUS PERFECTION!”
Top 10 direct quotes from Cohort 6
“I am grateful to be part of this cohort… Huge thanks to all of you!!!”
“I will be taking a lot of classes async… The recordings are posted so promptly and the Discord conversations stay active — exactly what you’d expect from a high-quality course!”
“I feel we’re the luckiest group to have Don and Laura in the same cohort — different styles, complementary strengths, and both incredibly patient.”
“Peer groups are awesome for discussion — the chats were fire.”
“Program is great. It moves fast, but I’d feel ripped off if I were too comfortable!”
“Great class, like always — really enjoying the cohort so far.”
“Shout out to everyone in AIM, including the peer supporters. What a great (but challenging) experience!”
“The sessions are going great. I’m learning a lot, and the peer supporters (Andre & Nithin) are so knowledgeable.”
“Mike is doing an excellent job — we’re really grokking the content in the breakouts!”
“Andre is amazing — super knowledgeable and incredibly patient in explaining everything to us.”
Who is this course for
What you’ll get out of this course
🧑💻 Become an AI-Assisted Developer
A vibe coder won’t take your job. An AI-assisted developer will.
🧑🤝🧑 Peer-Supported Live Coding
Work with certified AI Engineers in dedicated small Journey groups to discuss and code throughout the cohort!
🤩 Demo Day!
You will present a unique project live to a cohort of your peers and the public!
🕴️ industry Leading Curriculum
We’re always at The LLM Edge with the latest concepts, code, tools, techniques, and best practices!
💼 Hiring Opportunities
Certified AI Engineers get direct access to job opportunities from our network
What’s included
Live sessions
Learn directly from “Dr. Greg” Loughnane & Chris “The Wiz 🪄” Alexiuk in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
– Understand course structure – How to succeed as a certified AI Engineer on Demo Day!
– Meet your cohort, peer supporters, and journey group!
– LLM prototyping best practices, how to spin up quick end-to-end prototypes and vibe check them!
– Prompt Engineering best practices and the LLM Application Stack
– Understand embedding models and similarity search
– Understand Retrieval Augmented Generation = Dense Vector Retrieval + In-Context Learning
– Build a Python RAG app from scratch
Week 2
– Understand the state of production LLM application use cases in industry
– Ideate with peers & peer supporters
– Build an end-to-end RAG application using everything we’ve learned so far
– Why LangChain, OpenAI, QDrant, LangSmith
– Understand LangChain & LangGraph core constructs
– Introduce primary cohort use case
– Build a RAG system with LangChain and Qdrant
– Intro to LangSmith for evaluation and monitoring
Week 3
– Answer the question: “What is an agent?”
– Understand how to build production-grade agent applications using LangGraph
– Understand Context Engineering from first principles
– How to use LangSmith to evaluate agentic RAG applications
– Understand what multi-agent systems are and how they operate.
– Extend the primary cohort use case to a multi-agent solution
– Build a production-grade multi-agent applications using LangGraph
Week 4
– An overview of Synthetic Data Generation (SDG) – How to use SDG for Evaluation
– Generating high-quality synthetic test data sets for RAG applications in general and for our primary cohort use case specifically
– How to use LangSmith to baseline performance, make improvements, and then compare
– Build RAG and Agent applications with LangGraph
– Evaluate RAG and Agent applications quantitatively with the RAG ASsessment (RAGAS) framework
– Use metrics-driven development to improve agentic applications, measurably, with RAGAS
Week 5
– Understand how advanced retrieval and chunking techniques can enhance RAG
– Compare the performance of retrieval algorithms for RAG
– Understand the fine lines between chunking, retrieval, and ranking for our primary cohort use case
– Learn best practices for retrieval pipelines
– Discuss best-practice use of reasoning models
– Understand planning and reflection agents
– Build an Open-Source Deep Research agent application using LangGraph
– Investigate evaluating complex agent applications with the latest tools
Week 6
– Introduce the Certification Challenge
– Pitch your problem, audience, and solution
– Network with people outside of your group
– Understand the suite of tools for building agents with OpenAI and the evolution of their tooling
– Core constructs of the Agents SDK and comparison to other agent frameworks
– How to use monitoring and observability tools on the OpenAI platform
Week 7
– Understand Model Context Protocol (MCP) from client and server sides
– Learn MCP resource types and how to design useful MCP servers
– Build an MCP server that enhances allows us to enhance our search and retrieval toolbox for our primary cohort use case
– Learning how to monitor, visualize, debug, and interact with your LLM applications with LangSmith and LangGraph Studio
– Deploy your applications to APIs directly via LangGraph Platform
– Deploy an agent with MCP server for our primary cohort use case
Week 8
– Defining LLM Operations (LLM Ops) & Agent Operations (Agent Ops)
– Understand Agent2Agent Protocol (A2A), including how remote agents and client agents interact
– How to enable agent-to-agent communication with Agent cards and MCP
– Deploy an agent with MCP server for our primary cohort use case and then build another agent to act as a user of our application
– Understand guardrails, including the key categories of guardrails
– Understand the importance of caching – How to use Prompt and Embedding caching
– Apply guardrails and caching directly to our primary cohort use case
Week 9
– Understand how to deploy open LLMs and embeddings to scalable endpoints
– Discuss how to choose inference server
– Build an E2E enterprise agentic RAG application with LCEL
– Introduction to Building On-Prem
– Hardware & compute Considerations
– Local LLM & Embedding Model Hosting Comparison
– How to build and present an On-Prem Solution to stakeholders
Week 10
– Code Freeze
– Full Dress Rehearsal
Live AI Engineering Demo Day with industry judges, the public, and a cohort of your peers!
Build 🏗️, ship 🚢, and share 🚀 like a legend.
Active hands-on learning at the edge
We teach concepts AND code. Never one or the other. AI has accelerated so quickly that anyone who’s been a manager the last few years has not yet seen the code for themselves.
Project-based and community-driven
You’ll be interacting with other learners through breakout rooms and project teams. We can’t wait to see what you build, ship, and share on Demo Day projects 🤩.
Find fellow travelers for your journey
Join a community of like-minded AI practitioners who are all in on Generative AI, and who are heading down the same career path as you are.
Course Features
- Lectures 0
- Quizzes 0
- Duration 10 weeks
- Skill level All levels
- Language English
- Students 80
- Assessments Yes
