AI & Dev

RAG & LLM Applications

Advanced 2 days Online · 1-to-1 · Enterprise
RAG & LLM Applications

Overview

Build production-ready RAG pipelines and LLM-powered applications. Vector databases, embeddings, retrieval strategies, and deployment - for engineers ready to build real AI products.

Who Is This For

  • Developers who have completed the GenAI Intermediate level or equivalent
  • Engineers building AI-powered products and internal tools
  • Technical leads architecting LLM application infrastructure

Prerequisites

  • Python proficiency and experience with LLM APIs
  • Completion of Generative AI for Developers or equivalent knowledge
  • Familiarity with REST APIs and basic database concepts

Recommended Path

Best taken after
Generative AI for Developers

Learning Path

Advanced

2 days
  • Design RAG architectures: chunking strategies, embedding models, retrieval tuning
  • Implement vector databases (FAISS, Chroma, Pinecone) for production workloads
  • Build conversational AI with multi-turn context and source citation
  • Apply security, cost optimization, and monitoring for production LLM apps
  • Deploy a complete RAG application with evaluation and observability

By the end: You can architect and deploy production-grade RAG applications for enterprise use cases.

What You'll Receive

  • Hands-on lab exercises and a sample code repository to keep
  • Course slides and reference guides for every module
  • Session recordings for review after class
  • Certificate of completion
  • A post-course support window for follow-up questions

Delivery Options

Online Classes

Live, interactive sessions from anywhere. Small batches for personalized attention.

1-to-1 Coaching

Personalized mentorship with flexible scheduling tailored to your goals.

Enterprise Training

Customized programs for teams, delivered online or on-site, scoped to your stack.

Your Instructor

Taught by a practicing engineer with hands-on experience building and scaling test automation, CI/CD, and AI-assisted tooling across enterprise teams. Every session is delivered by the instructor - no recordings-only courses, no junior stand-ins - with real-world examples drawn from production projects.

What Learners Say

"The RAG architecture section gave me everything I needed to replace our naive LLM integration with a proper retrieval pipeline. Halluciations dropped overnight."

DL

Darren Liu

AI Engineer

"Vector database selection and chunking strategies were the pieces I was missing. The hands-on Pinecone labs were directly applicable to our product."

FO

Fatima Omar

Technical Lead

Frequently Asked Questions

This is an Advanced-level course. You should have Python proficiency and prior LLM API experience - ideally from completing Generative AI for Developers or equivalent work. We can advise on readiness during a free consultation.

Both. We deliver live online classes, 1-to-1 coaching, and on-site or remote enterprise sessions for teams.

Yes. For enterprise engagements we tailor examples, exercises, and the detailed outline to your application, tools, and timeline.

Yes - a certificate of completion is provided at the end of the course.

Python proficiency, experience with LLM APIs, and completion of the Generative AI for Developers course (or equivalent). Familiarity with REST APIs and basic database concepts is expected.

Related Courses

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Request the detailed day-by-day outline or book a free consultation to confirm readiness for this Advanced course.

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