Here’s What You Get:
What It Is
The Aurimas Griciunas – End-to-End AI Engineering Bootcamp is an 8-week intensive, cohort-based training designed to transform technical professionals into full-stack AI engineers capable of designing, building, and deploying real-world AI applications (not just demos).
Leader: Aurimas Griciūnas — LinkedIn Top Voice in AI, Founder & CEO of SwirlAI, and former CPO at Neptune.ai.
Format: Weekly sprint-based curriculum with live sessions, labs, Q&A, hands-on coding, and a capstone project.
Audience: Data scientists, ML engineers, data engineers, software engineers, and technical professionals looking to build and ship production-ready AI systems.
Core Learning Goals
This bootcamp emphasizes end-to-end AI engineering skills, including:
Production-Ready AI Development
Build real AI apps using large language model (LLM) APIs (e.g., GPT, Claude, Gemini).
Integrate vector databases, RAG (Retrieval-Augmented Generation) systems, and agent frameworks such as LangChain and LangGraph.
Deploy services with Docker, FastAPI, Kubernetes, and cloud infrastructure.
Advanced Architecture Patterns
Design and evaluate agentic and multi-agent systems for complex workflows.
Learn hybrid retrieval techniques (dense + BM25), reranking, and synthetic data methods to enhance RAG accuracy.
Implement structured prompt and context engineering for robust model input/output handling.
LLMOps & Reliability
Add observability, performance monitoring, and quality evaluation to AI systems.
Integrate evaluation gates in CI/CD pipelines for continuous testing and deployment.
Build systems with real-world reliability rather than simplistic prototypes.
Capstone Project
Build, document, and deploy a real AI application over the sprint-based curriculum.
Present your project on Demo Day with a working code repository and live demo — great for portfolios and hiring.
Learning Structure
Each week models real engineering sprints:
Sprint Lesson (Mon): Self-paced videos, cheatsheets, and reference code.
Sprint Review (Tue): Live walkthrough and in-depth Q&A with Aurimas.
Sprint Build Lab (Thu): Live coding with guided implementation.
Weekly time commitment: ~5 hrs live + ~7 hrs project work.
What You Get
Live sessions with direct access to the instructor.
30+ hours of pre-recorded coding labs, plus extensive reading material (~250+ pages).
Lifetime access to content and recordings.
Compute credits (e.g., $500 in Modal credits for deployment).
Completion certificate to demonstrate your skills.
Community and peer network for collaboration and accountability.
Why It’s Valuable
Focuses on building deployable systems, not academic concepts or toy examples.
Covers modern production tools and practices like observability, LLMOps, structured prompts, and agent orchestration — skills sought by today’s AI teams.
Designed around real engineering patterns used in industry rather than isolated coding exercises.
Who Should Join
This bootcamp is especially suited to professionals who want to:
Transition into AI engineering roles from ML or data backgrounds.
Level up their ability to build scalable, reliable AI products.
Demonstrate real portfolio projects to potential employers or investors.











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