Agentic AI is rapidly transforming how work gets done, marking a pivotal shift in the evolution of intelligent systems. Mastering this new paradigm has never been more essential. This course empowers you with the practical skills and strategic understanding needed to design, build, and deploy real-world agentic AI systems, unlocking powerful opportunities for innovation, automation, and career growth.
What’s in this course?
We begin with the core foundations of Agentic AI - understanding what agents are, how they differ from traditional AI systems, and how reasoning, planning, and tool usage enable autonomous workflows. From there, we explore the building blocks of agentic systems, including LLMs, memory, embeddings, vector databases, and RAG pipelines. You’ll learn how agents reason, how they use tools, and how to structure prompts and task orchestration for optimal performance.
Next, we move into advanced, real-world demonstrations, where you will build practical agentic solutions such as:
Standalone AI Agents
An MCP Server and Client Agent
Multi-Agent Systems using CrewAI
An AWS Monitoring Multi-Agent System
A Cross-Cloud Multi-Agent System using AWS and Google Cloud
Agentic RAG systems for intelligent knowledge retrieval
A Course Intelligence Agent using Agentic RAG
A Project Feasibility Analysis Agent powered by Agentic RAG
These demonstrations simulate real enterprise and startup use cases, helping you understand how agentic AI systems are designed, scaled, and deployed in production environments.
By the end of this course, you’ll be able to:
Build autonomous AI agents from scratch
Use Smolagents, MCP, CrewAI, and n8n to create production-grade agentic systems
Integrate RAG, memory systems, embeddings, and tool-based reasoning
Design multi-agent workflows where agents collaborate intelligently
Build cloud-aware and cross-cloud agentic systems
Deploy agents using Docker or cloud environments
Implement guardrails, safety, debugging, and reflection-based optimization
Build scalable, real-world automation powered by Agentic AI
Special Note
This course is highly practical, packed with real demonstrations, hands-on projects, troubleshooting scenarios, and end-to-end agent-building exercises. You won’t just learn how agents work - you’ll build them, optimize them, and deploy them in real-world applications.
Course Structure:
Concept Lectures
Step-by-step Demonstrations
Real-world Agentic AI Projects
Practical Scenarios & Troubleshooting
Course Contents:
Fundamentals of Agentic AI
LLMs and Core Foundations
Building AI Agents from Scratch
Smolagents Framework
Memory, Embeddings & Vector Databases
Retrieval-Augmented Generation (RAG)
Model Context Protocol (MCP)
Multi-Agent Systems
Cloud & Cross-Cloud Multi-Agent Architectures
Tool Use & Orchestration
Reflection, Safety & Guardrails
Deployment Techniques
Real-world Projects & Demonstrations
All sections of this course are demonstrated live, with the goal of encouraging enrolled users to set up their own environments, complete the exercises, and learn through hands-on experience!