Dr. Greg and The Wiz Maven – The AI Engineering Bootcamp (2025)

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Dr. Greg and The Wiz Maven – The AI Engineering Bootcamp (2025)

Dr. Greg and The Wiz Maven - The AI Engineering Bootcamp (2025)

Dr. Greg and The Wiz Maven – The AI Engineering Bootcamp (2025)

Original price was: $3,999.00.Current price is: $87.00.

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Original price was: $3,999.00.Current price is: $87.00.

Learning how to monitor, visualize, debug, and interact with your LLM applications with LangSmith…

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Description

Dr. Greg and The Wiz Maven – The AI Engineering Bootcamp (2025)

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.

πŸ§‘β€πŸ’»Β 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 β€œNo,” this class is not for you.

πŸ’ΌΒ ON LEADING AI ENGINEERING TEAMS

– Do you manage a team of people that writes code every day?

If β€œYes,” this class might be for them.

β€”β€”

**KEY CURRICULUM UPDATES FOR COHORT 8**

πŸ› οΈΒ 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

πŸ€–Β Deep Agents

πŸ“ŠΒ Evaluating the EvaluatorsΒ (Aug 2025) &Β In Defense of EvalsΒ (Sep 2025)

πŸ† Demo DayΒ Semi-Final CompetitionΒ Round

A brand newΒ primary cohort use caseΒ that builds on itself and runs throughout the cohort:Β Deep Research from Scratch

**KEY CURRICULUM UPDATES FOR COHORT 7**

🟒 [New Additions]

– Context EngineeringΒ from first principles

– AΒ primary cohort use caseΒ that builds on itself and runs throughout the cohort

– Expansion ofΒ Model Context Protocol (MCP)Β content

– UsingΒ Agent2Agent (A2A) ProtocolΒ toΒ build and run two agents, one w/ MCP server and one toΒ mimic a human using our agent

– DedicatedΒ GuardrailsΒ session, from best-practices to implementation

πŸ”΄ [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

β€”β€”

OUR COMMUNITY

πŸ—οΈ πŸš’πŸš€ AI Makerspace is on aΒ 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 itΒ willΒ transform you! It will get you comfortable thriving at β€œThe 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 πŸ—οΈ, Ship 🚒, Share πŸš€!

This is the secret to success in a 21st-century workforce, and you will live this every class, every week of the cohort!

πŸ§‘β€πŸ€β€πŸ§‘ 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.

πŸ™‹ 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

πŸ™‹ 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:

πŸ“œΒ Curriculum & Detailed Schedule:Β 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:Β https://bit.ly/aie-cohort-3-reflections

– Ches Roldan’s β€œ20 Tips to Survive AI Makerspace’s AI Engineering Bootcamp (as a non-technical person)”:Β https://bit.ly/aie-20tips

πŸ’° 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 beenΒ Software EngineersΒ andΒ DevelopersΒ orΒ Data ScientistsΒ andΒ 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 toΒ 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

β€œOne 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.”

β€œThis session was pure gold, seeing actual applications, really nice!”

β€œI am having lots of fun and learning. LOVE THE ENERGY! Let’s go.”

β€œThe breakout rooms are absolutely fantastic. Peer Supporters are bae.”

β€œThe breakout rooms are just so good – easily sets it apart from 90% of other courses out there.”

β€œIt was a great session today. Super helpful and getting clearer. Amazing job everyone. Love this!!!!”

β€œI 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.”

β€œThis class was worth every dollar, thank you guys!”

β€œThank you for an amazing ride! <3”

β€œI 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

β€œI am grateful to be part of this cohort… Huge thanks to all of you!!!”

β€œI will be taking a lot of classes async… The recordings are posted so promptly and the Discord conversations stay active β€” exactly what you’d expect from a high-quality course!”

β€œI feel we’re the luckiest group to have Don and Laura in the same cohort β€” different styles, complementary strengths, and both incredibly patient.”

β€œPeer groups are awesome for discussion β€” the chats were fire.”

β€œProgram is great. It moves fast, but I’d feel ripped off if I were too comfortable!”

β€œGreat class, like always β€” really enjoying the cohort so far.”

β€œShout out to everyone in AIM, including the peer supporters. What a great (but challenging) experience!”

β€œThe sessions are going great. I’m learning a lot, and the peer supporters (Andre & Nithin) are so knowledgeable.”

β€œMike is doing an excellent job β€” we’re really grokking the content in the breakouts!”

β€œAndre is amazing β€” super knowledgeable and incredibly patient in explaining everything to us.”

Who is this course for

What you’ll get out of this course

πŸ§‘β€πŸ’» Become an AI-Assisted Developer

A vibe coder won’t take your job. An AI-assisted developer will.

πŸ§‘β€πŸ€β€πŸ§‘ Peer-Supported Live Coding

Work with certified AI Engineers inΒ dedicated small Journey groupsΒ 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!

πŸ•΄οΈ industry Leading Curriculum

We’re always atΒ The LLM EdgeΒ  with the latest concepts, code, tools, techniques, and best practices!

πŸ’Ό Hiring Opportunities

Certified AI Engineers get direct access to job opportunities from our network

What’s included

Live sessions

Learn directly from β€œDr. Greg” Loughnane & Chris β€œThe Wiz πŸͺ„” 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 theΒ Maven Guarantee.Β Students are eligible for a full refund up until the halfway point of the course.

Course syllabus

Week 1

Live Session 1: πŸ€– Introduction & Vibe Check

– 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!

Live Session 2: πŸ—ƒοΈ Embeddings and Retrieval Augmented Generation (RAG)

– 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

Live Session 3: πŸš€ Industry Use Cases & End-to-End RAG

– 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

Live Session 4: πŸ”— Production-Grade RAG with LangGraph

– Why LangChain, OpenAI, QDrant, LangSmith

– Understand LangChain & LangGraph core constructs

– IntroduceΒ primary cohort use case

– Build a RAG system with LangChain and Qdrant

– Intro to LangSmith for evaluation and monitoring

Week 3

Live Session 5: πŸ•΄οΈ Production-Grade Agents with LangGraph

– Answer the question: β€œWhat 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

Live Session 6: πŸ”„ Multi-Agent Applications

– Understand what multi-agent systems are and how they operate.

– Extend theΒ primary cohort use caseΒ to a multi-agent solution

– Build a production-grade multi-agent applications using LangGraph

Week 4

Live Session 7: πŸͺ„ Synthetic Data Generation for Evaluation

– 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 ourΒ primary cohort use caseΒ specifically

– How to use LangSmith to baseline performance, make improvements, and then compare

Live Session 8: πŸ“Š RAG and Agent Evaluation

– 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

Live Session 9: πŸ• Advanced Retrieval Strategies for RAG Apps

– 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 ourΒ primary cohort use case

– Learn best practices for retrieval pipelines

Live Session 10: 🧠 Advanced Agentic Reasoning

– 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

Live Session 11: πŸ§‘β€πŸŽ“ Certification Challenge

– Introduce the Certification Challenge
– Pitch your problem, audience, and solution
– Network with people outside of your group

Live Session 12: πŸ€– OpenAI Agents SDK

– 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

Live Session 13: πŸŒ€Β Model Context Protocol (MCP)

– 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 ourΒ primary cohort use case

Live Session 14: 🚒 Deploying Agents to Production

– 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 ourΒ primary cohort use case

Week 8

Live Session 15: πŸ”€Β Agent2Agent (A2A) Protocol & Agent Ops

– 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 ourΒ primary cohort use caseΒ and then build another agent toΒ act as a userΒ of our application

Live Session 16: πŸ›€οΈΒ Guardrails & Caching

– 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 ourΒ primary cohort use case

Week 9

Session 17: πŸ”“Β Open-Source Model Endpoints

– 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

Session 18: 🏒 On-Prem Agent Applications

– 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

Live Session 19: 🎀 Demo Day Dress Rehearsal

– Code Freeze
– Full Dress Rehearsal

Live Session 20: πŸ“Έ Demo Day & Graduation Ceremony

Live AI Engineering Demo Day with industry judges, the public, and a cohort of your peers!

Build πŸ—οΈ, ship 🚒, and share πŸš€ like a legend.

Build πŸ—οΈ, ship 🚒, and share πŸš€ 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.

 

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