Small in-person cohorts with limited seats. Pick a course below and register on WhatsApp — we will confirm your seat and share the details.
Retrieval-Augmented Generation is how real companies put large language models to work on their own data — securely, accurately, and at scale. It is the single most in-demand AI skill today.
RAG grounds LLMs in a company's own data — accurate, current, and secure. It's how AI ships in the real world.
AI and RAG engineers are among the most sought-after and best-paid roles across every industry today.
No slide-only lectures. You build embeddings, vector search, and full RAG pipelines from day one.
Guided by engineers who build AI for Fortune clients — you learn what actually works in production.
Whether you are shipping code, starting your career, or upskilling a whole team — this program meets you where you are.
Add AI and RAG to your toolkit and move into the highest-value engineering roles. Ideal if you already write code and want to build intelligent applications.
Graduate with a job-ready, in-demand skill and a real project in your portfolio. We start from fundamentals — no prior AI experience needed.
Upskill your whole team on AI and RAG with a private, in-person batch tailored to your stack, data, and business goals.
Eight progressive modules take you from LLM fundamentals to a deployed, production-ready RAG application. Every module is hands-on and taught in-person.
Full syllabus in the brochureHow large language models work, tokens, context windows, and where they fit in real products.
Designing reliable prompts, structured outputs, and context strategies that reduce hallucination.
Turn text into vectors and search it — Pinecone, pgvector, Chroma, and similarity search in practice.
Chunking, retrieval, re-ranking, and generation — assemble an end-to-end Retrieval-Augmented Generation system.
Hybrid search, query rewriting, and how to measure and improve RAG answer quality.
When to fine-tune vs. retrieve, dataset prep, and adapting models to a domain.
APIs, caching, cost control, guardrails, and shipping AI features to production safely.
Design, build, and present a complete RAG application on a real-world use case of your choice.
Taught by practicing engineers from Perception System who build and ship AI systems for Fortune companies — not full-time trainers.
10+ yrs · LLM & RAG systems
Builds production AI platforms and retrieval systems for enterprise clients.
12+ yrs · Application Architecture
Specialises in vector search, embeddings, and scalable retrieval architecture.
10+ yrs · Backend Development
Powering scalable, secure, and high-performance backend systems
