Master Production Grade AI Systems

Our curriculum focuses on practical application, so you master the tools powering today's AI systems and ship them with confidence.

LLM Integration

Agentic Workflows

Deployment & APIs

Vector Databases

Build with OpenAI and Claude APIs, including streaming, structured outputs with Pydantic and function calling. Understand tokens, context windows and how to choose between closed, open, small and large models.

Build AI agents and multi-agent systems with LangGraph, connect tools through the Model Context Protocol (MCP) and automate business workflows with n8n.

Serve AI through FastAPI with streaming, authentication and rate limiting. Containerise with Docker and deploy to AWS with CI/CD pipelines and evaluation gates.

Build RAG pipelines with Qdrant and pgvector, combining BM25 keyword search, hybrid search and reranking for accurate, well-cited answers.

Everything Included in the Course

LMS Access & Recordings

A dedicated learning portal tracks your progress, modules and resources. Every live class is recorded and available on to revisit.

Assignments and 9 Practical Projects

Hands-on, graded projects that build real systems: RAG pipelines, agents and deployed AI APIs, each one adding a working system to your portfolio.

Complete Handbook and Cheatsheets

A structured written companion covering the full curriculum end to end, plus quick-reference guides for prompts, APIs, RAG pipelines and deployment.

Capstone Project and Career Readiness

Design and build a complete AI system, present it on demo day, and get job-ready with GitHub portfolio building, README writing and LinkedIn positioning.

Our 16-week curriculum equips you with production-grade skills for the most high-demand engineering positions in artificial intelligence today.

AI Engineer

Generative AI Developer

LLM ApplicationDeveloper

AI Agent Developer

RAG Engineer

AI Automation Specialist

AI Solutions Engineer

Gain production-grade competencies designed to take you from foundational AI concepts to shipping resilient, scalable LLM architecture.

LLM Application Building

RAG Systems & Evaluation

Autonomous AI Agents

Build AI applications using OpenAI, Claude and open-source models

Design and evaluate RAG systems on real business documents

Build AI agents and multi-agent systems with LangGraph and MCP

Workflow Automation

Security & Monitoring

Cloud Deployment

Cost & Latency Control

Automate business workflows using n8n and AI

Test, secure and monitor AI systems

Deploy AI applications to the cloud with Docker and CI/CD

Reduce AI costs through caching, model routing and fine-tuning

Ready to Engineer Your AI Future?

Download our detailed syllabus to explore the full curriculum and career outcomes you'll achieve.