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Cohort 01 — Starts May 5, 2026

Build real AI.
Engineer the future.

For developers who've already called an LLM and want to go further. RAG, agents, agentic design patterns, multi-agent systems, MCP, LangGraph, guardrails, and deployment — you build it, evaluate it, and present it live.

5wk
Intensive bootcamp
4+
Real-world projects
1:1
Expert feedback
How it works

From API calls to production —
in 5 weeks.

No intro content. No passive watching. You build production-grade systems, ship them, and get reviewed by working engineers.

01

Register & join your cohort

Apply, get accepted, and join a cohort of serious AI builders.

02

Learn through live sessions

Weekly live classes taught by your instructor — a working AI engineer and CS professor.

03

Deliver real projects

Each module ends with a graded project. Build RAG apps, agents, and full pipelines.

04

Get expert feedback

Detailed code review and written feedback on every submission. No auto-graders.

Course syllabus

5 weeks. Real skills.
Shipped projects.

One 2-hour live session per week — lecture + demo on Thursdays 7–9 PM ET. Lab completed async, graded project submitted before the next session. Every assignment includes an evaluation component — you don't just build it, you prove it works.

AI Engineering Bootcamp — Cohort 01

5 weeks Live online Starts May 5 Thu 7–9 PM ET Sessions recorded Labs ~3–4 hrs Python or TS required ↓ Download Syllabus
Kickoff — Onboarding & Dev Environment Setup
Tools, repos, API keys, Python environment, first LLM call
Live session
W1
Week 1 — Advanced Prompt Engineering & API Patterns
Production prompt design · structured outputs · model selection · cost vs quality tradeoffs · live API setup
Graded assignment
1.1
Lecture + Live Demo — Production prompt engineering
Model selection, context window strategy, temperature tradeoffs, system prompt design, live API demo
Lecture
1.2
Assignment — Build a prompt-powered CLI tool
Multi-step prompt chains, structured JSON output, model fallback, error handling · written design rationale: what you built, key decisions, what you'd change
Assignment
W2
Week 2 — RAG: Retrieval-Augmented Generation
Embeddings · vector databases · chunking strategies · retrieval pipelines · RAGAS evaluation
Graded assignment
2.1
Lecture — How RAG works end-to-end
Embeddings, semantic search, chunking strategies, retrieval quality tradeoffs
Lecture
2.2
Demo — Build a RAG pipeline live
Ingest a PDF, embed it, store in ChromaDB, query it, return cited answer
Lecture
2.3
Assignment — Build a RAG app over your own documents
Groups of up to 5 · ingest your own docs · ChromaDB vector store · cited answers · Pure Python or LlamaIndex · run RAGAS eval · analyze your lowest score, fix it, re-run · written rationale per person
Assignment
W3
Week 3 — AI Agents, Agentic Design Patterns & MCP
Agentic loops · function calling · Reflection · Planning · Model Context Protocol · Kiro · hooks · LangSmith tracing
Graded assignment
3.1
Lecture — Agents, agentic design patterns & MCP
ReAct loops, function/tool calling, Reflection pattern (agent critiques its own output), Planning pattern (task decomposition), MCP architecture, connecting MCP servers
Lecture
3.2
Demo — Kiro: spec-driven dev, hooks & MCP wiring
Live instructor demo of Kiro IDE · spec-based development · hooks · connecting MCP servers in an agentic IDE
Lecture
3.3
Assignment — Build an agent that calls your RAG system via MCP
Wrap your Week 2 RAG app as an MCP tool · agent reasons over your documents · cited answers · add LangSmith tracing · submit a trace showing one failed query and your diagnosis · fallback implementation provided if needed
Assignment
W4
Week 4 — Multi-Agent Systems, Production & Deployment
LangGraph · multi-agent orchestration · supervisor/subagent routing · safety & guardrails · evaluation · observability · Railway deployment
Graded assignment
4.1
Lecture — Multi-agent systems & production agentic software
Supervisor/subagent routing, shared state, multi-agent LangGraph workflows, safety guardrails, prompt injection defense, hallucination control, evaluation harness, observability, cost control, Railway + FastAPI deployment
Lecture
4.2
Demo — Refactor your agent into a LangGraph workflow
Retrieve → reason → respond nodes · conditional retry on low confidence · run eval test cases · observe cost and latency per node
Lecture
4.3
Demo — Build a multi-agent research assistant
Supervisor agent routes to specialist subagents: search agent, RAG agent (from Week 2), critic agent · shared LangGraph state · Reflection loop · critic flags weak outputs and re-routes for revision
Lecture
4.4
Assignment — Orchestrate, evaluate, and deploy your agent
Refactor Week 3 agent into LangGraph workflow · add supervisor routing · eval harness with min 10 test cases · wrap as FastAPI · deploy to Railway · submit live URL
Assignment
W5
Week 5 — Demo Day
Present your live deployed agent · walk through architecture · defend your decisions · get expert feedback
Capstone
5.1
Demo Day — Live group presentations
10 minutes per group · live demo of your deployed app · architecture walkthrough · show your eval scores · defend your design decisions · Q&A with mentors · graded after the session
Assignment
+
Also included with every cohort
Weekly Q&A with mentors · TA office hours · guest tech talks · career & LinkedIn session · private Discord community
Included
↓ Download full curriculum
Why AiBricks

Built for engineers,
not beginners.

Every decision made for developers who already know how to code and want to build real AI systems — not watch intro videos.

Cohort-based learning

You learn with a group, not alone. Accountability, peer reviews, and shared momentum built in.

Graded projects, real feedback

Every project is marked by an expert — not an LLM. Expect detailed, honest critique.

Taught by a practitioner

Your instructor is a CS professor and industry AI engineer. Theory meets real production experience.

No fluff, no filler

Deliberately short curriculum. Only what matters. Every hour spent is an hour that compounds.

Small cohorts only

Max 100 students per cohort. Real access to the instructor, not just a Slack channel.

Private Discord community

Cohort-only Discord server — ask questions, share progress, and get help between sessions. Active 24/7.

Anthropic API credits included

API credits provided for all lab work — no out-of-pocket API costs for coursework. Additional usage beyond labs at student's expense.

Portfolio on graduation

Leave with 4+ shipped projects — RAG apps, agents, deployed APIs — ready to show employers.

Your instructors

Learn from people
who ship in production.

Not content creators. Working AI engineers with real industry experience. Each cohort also includes guest talks from leading figures in AI engineering and agentic AI.

Dr. Reza Ahmadi
Reza Ahmadi, PhD
Principal AI Engineer · Professor, Queen's University

With 15+ years of industry experience, Reza works at the intersection of industry and academia — building production AI systems by day, teaching software engineering at Queen's. He has trained 200+ professionals in AI engineering.

LLMs & Agents Production AI MLOps ↗ LinkedIn
Sami Riaz
Sami Riaz
AI Engineer in Industry · McGill University Alumni

Sami brings 7 years of professional software engineering experience to AiBricks. Currently working as an AI engineer in industry with a strong foundation from McGill University.

AI Engineering Software Engineering 7 Years Industry ↗ LinkedIn
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Guest Speakers
Leading figures in AI engineering & agentic AI

Each cohort includes exclusive guest talks from practitioners at the frontier of AI engineering. Names to be announced.

Pricing

One cohort. Two options.
Zero fluff.

Cohort 01 is priced to get serious people in the room. Price increases for Cohort 02.

Not satisfied after Week 1? Full refund — no questions asked.
Email us within 7 days of the first session. We'll refund your payment in full.
COHORT 01 PRICE
Early access
$1,097 USD
one-time · limited seats · all sessions recorded
Regular price $1,997 USD
  • 5 weeks of live instruction
  • 3 graded projects + capstone
  • Expert feedback on every submission
  • Weekly Q&A with mentors
  • TA office hours
  • Guest tech talks
  • Portfolio of shipped AI projects
  • Anthropic API credits included for labs
  • Private Discord community
Payment plan
$365
USD × 3 months
$1,095 USD total · split over 3 months
Same full access. First payment due at enrollment. Remaining two payments billed monthly. No hidden fees.
  • Everything in the full plan
  • Split into 3 monthly payments
  • No interest, no penalty
Cohort 01 — max 100 students · 5 spots taken · Regular price $1,997 USD from Cohort 02 onwards
TEAMS & ORGANIZATIONS
Training your whole engineering team?
Custom cohorts available for companies. Same curriculum, delivered privately for your team — on your schedule.
Get in touch →
What people say

What people say.

Anonymous feedback from Queen's University students, and direct feedback from industry professionals after sessions with Reza.

"Even I was able to run the AI analysis today — and I'm not technical at all. I love it! Thanks Reza for the knowledge transfer."

— Rena · Engineer

"I'm finding the tool we made during the session more useful than Kiro for initial investigations right now. Hats off Reza for however you did that. I'd love to get a deeper understanding of how it works."

— James · Engineer

"Obviously cares a lot about the course. Quick to respond to questions. Assignments are well-written and unambiguous. The course is not very stressful."

— Software Engineering Student at Queen's University

"Great instructor — cares very much about the content. Well organized. Interesting material."

— Software Engineering Student at Queen's University

"Super helpful content, presented in a clear manner."

— Software Engineering Student at Queen's University
FAQ

Common questions.

Who is this for?
This is an advanced bootcamp for developers who have already used LLMs — called an API, built a toy project, or experimented with ChatGPT. You write Python or TypeScript daily and you're ready to go beyond tutorials and build systems that work in production. If you've never written code before, this is not the right course. Time commitment: 2 hrs live Thursdays 7–9 PM ET plus 3–4 hrs async lab per week. All sessions recorded.
What if I'm not satisfied?
Full refund if you email us within 7 days of the Week 1 session. No forms, no explanations required. We've made this easy on purpose — we want serious learners, not reluctant ones.
What if I miss a live session?
Every session is recorded and shared with the cohort within 24 hours. You won't fall behind. Labs are async and due before the next session.
Do I need a machine learning background?
No. This is an AI Engineering bootcamp — you'll learn to build systems that use AI, not train models. Python or TypeScript basics are all you need to start.
How does the payment plan work?
First payment ($365 USD) is due at enrollment and gives you immediate full access. Payments 2 and 3 are billed automatically each month via Stripe. All 3 payments are committed at enrollment — this is a structured plan, not a subscription you can cancel.
Do I get a certificate?
Yes. Students who complete all projects receive an AiBricks AI Engineering certificate. Cohort 01 graduates will also receive a Credly digital badge suitable for LinkedIn.
Is payment handled securely?
Yes. All payments are processed via Stripe — we never see or store your card details. You'll receive a Stripe receipt immediately after payment.

Ready to build seriously?

Cohort 01 is forming now. 95 spots remaining out of 100.