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Build and ship real, production-grade AI products in just 8 weeks—master LLMs, RAG, agents, and deployment by creating a live, end-to-end AI application you can proudly show to employers or investors.
End-to-End AI Engineering Bootcamp – Aurimas Griciunas
🚀 Build Real AI Products, Not Just Prototypes
The End-to-End AI Engineering Bootcamp is an 8-week, cohort-based experience designed to turn technical professionals into full-stack AI engineers who can confidently design, build, and deploy production-grade AI systems.
🛠️ What You’ll Build
You’ll develop your own capstone project – a real-world AI application built sprint by sprint, applying each week’s concept to solve a business-relevant use case. By the end, you’ll present it live on Demo Day, with a working repo and deployed app you can showcase to hiring managers, CTOs, or investors.
🧑💻Technologies include:
✔️ LLM APIs (Gemini, Claude, GPT, etc.).
✔️ Vector databases & RAG.
✔️ AI agent libraries (LangChain, LangGraph, ADK).
✔️ Docker, FastAPI, Kubernetes, cloud deployment.
✔️ Observability, evaluation, and performance testing.
✔️ Modern communication protocols (A2A, MCP).
🧠 How It Works
Each week follows a real engineering sprint:
Sprint Lesson (Monday): Self-paced learning with videos, cheatsheets & reference code.
Sprint Review (Tuesday): Live walkthrough with Aurimas + deep Q&A.
Sprint Build Lab (Thursday): Live coding session to implement key sprint features.
Bonus QnA and Feedback sessions.
What you’ll learn
Master end-to-end AI engineering – transform prototypes into production-ready apps with LLMs, RAG & agents in just 8 weeks.
Design and optimize RAG architectures
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Learn how to systematically evaluate and improve RAG based systems.
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Apply techniques like Hybrid Retrieval (BM25 + Dense Embeddings) and Reranking to optimise Retrieval process of your RAG Systems.
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Utilize synthetic data generation to help you improve the system without needing real user data.
Engineer and orchestrate agentic systems
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Create agents that can plan steps, use tools and complete tasks on their own.
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Evolve your RAG into Agentic RAG System to support complex user queries grounded in context from different data sources.
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Connect your Agentic Systems to tools via MCP.
Design and deploy multi-agent systems for complex workflows
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Learn patterns for designing Multi-Agent Systems and how to add safeguards so that they act predictably.
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Implement A2A (Agent to Agent) protocol to allow your agents to communicate with other remote agents.
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Implement evaluation strategies targeting multi-agent systems.
Implement structured prompt and context management
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Learn to use structured outputs so the model’s responses fit cleanly into downstream systems.
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Apply best practices for prompt versioning and evolution.
Apply LLMOps for observability and continuous evaluation
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Learn how to Evaluate GenAI applications of different complexities and architectures.
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Implement Eval Quality Gates as part of your CI/CD pipeline.
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Add Observability to your systems from the first week.
Build and deploy production-grade GenAI applications
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Set up APIs and services so they run reliably in production.
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Deploy your application to the cloud and expose it to potential users.
Learn directly from Aurimas
LinkedIn Top Voice in AI • Founder & CEO @ SwirlAI
Who this course is for
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Data Professionals (Analysts & Scientists)
Looking to move beyond analysis and modeling to build and deploy real-world AI systems.
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ML Engineers
Who want to deepen GenAI skills and master scalable, production-ready AI engineering from end to end.
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Data Engineers
Ready to expand into AI by learning how to integrate data pipelines with LLMs, RAG, and agent-based systems.
What’s included
Live sessions
Learn directly from Aurimas Griciunas in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Code-along Recordings
30+ Hours of pre-recorded coding videos that you can follow while building out your Capstone.
Extensive Reading Materials
200+ Pages of reading material that you can refer to during and after the Bootcamp.
Compute Credits
$500 in Modal Compute Credits.
SwirlAI Talent Collective
Opportunity to join SwirlAI Talent Collective where we connect the most talented students with companies seeking exceptional talent in AI Engineering.
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.
Course Features
- Lecture 0
- Quiz 0
- Duration 10 weeks
- Skill level All levels
- Language English
- Students 76
- Assessments Yes