About the course

Building Next-Generation AI Systems with RAG, Multi-Agent Workflows, and Observability Tools

Unlock the future of AI engineering with this comprehensive course that delves into cutting-edge techniques shaping modern generative AI systems. Designed for experienced engineers and AI practitioners, this course provides deep technical insights into Retrieval-Augmented Generation (RAG) architecture, multi-agent workflows, and observability best practices using industry-leading tools like Langflow, Langfuse, and Langwatch.

Become a job-ready GenAI Engineer with hands-on training in building, deploying, and monitoring real-world AI systems.
This intensive program equips you with practical expertise across the full GenAI development lifecycle — from prompt engineering and embeddings to Retrieval-Augmented Generation (RAG), autonomous agents, and observability.

🚀 What You Will Learn

This immersive program is divided into 4 core modules with 16 expert-led sessions — plus 2 bonus sessions!

New content drops every week (2 sessions/week)

so you can learn at your pace and apply as you go.

📘 Module 1: Foundation (Weeks 1–2)

• Understand Generative AI fundamentals

• Learn prompt engineering, embeddings, and vector databases

🧠 Module 2: Building RAG Applications (Weeks 3–4)

• Develop and scale Retrieval-Augmented Generation systems

• Explore top RAG frameworks and integration strategies

🤖 Module 3: Agentic AI (Weeks 5–6)

• Create autonomous AI agents

• Orchestrate multi-agent workflows for real-world use cases

📊 Module 4: Observability & Capstone Project (Weeks 7–8)

• Implement observability and monitoring in GenAI pipelines

• Build your final project to showcase your skills

🎁 Bonus Sessions:

• LangServe – Serve LangChain apps effortlessly

• MCP & A2S – Master memory, chaining, and structured agents