← Back to the catalogueAI Agents & Automation
Classroom . Online . Hybrid
Mode
Course overview
A build course on autonomous agents and the automation layer that puts them to work. Learners implement the agent loop from first principles, then move to frameworks LangGraph, CrewAI, AutoGen and the OpenAI Agents SDK — adding tools, memory, planning and human approval. The second half connects agents to business systems through n8n, Zapier and webhooks.
Four agents are built during the course: research, email triage, HR assistant and a multi-agent operations crew.
Who it is for
- Developers with Python and API experience
- Automation engineers
- Operations and IT teams
- AI application developers
Prerequisites
Python fundamentals and REST API basics. Prompt engineering exposure is helpful.
How it runs
Learn → Practise → Build → Experience → Demonstrate, ending in a capstone. Delivered by practitioners from the engineering bench, in Madurai, Coimbatore and online.
Final project
Multi-Agent Operations Assistant
Programme sheet
The printed sheet carries the full module breakdown, labs, project work and certification path. Fees, dates and formats for the next intake are confirmed by the education team on enquiry.
Learning outcomes
01
Implement an agent loop with tool calling and memory.
02
Build multi-agent systems with defined roles.
03
Connect agents to email, calendars, CRMs and databases.
04
Monitor agent runs, cost and failure cases.
05
Design tools with safe, typed interfaces.
06
Add planning, retries and human approval steps.
07
Automate workflows with n8n and Zapier.
Module structure
8 modulesModule 01
Agent Fundamentals
What makes an agent . Planning . Tool use . Reason-act loops . Memory types . Guardrails and termination
Module 02
Tool and Function Calling
Function schemas . Error handling . Tool selection . Argument validation . Parallel calls
Lab
Weather and Search Tools
Module 03
Memory and State
Short-term context . Vector memory . Persistence . State machines
Lab
Agent with Durable Memory . Conversation Memory
LangChain . OpenAI Agents SDK . LangGraph . AutoGen
Lab
Same Agent in Two Frameworks . Choosing a Framework
Module 05
Multi-Agent Systems
Roles and delegation . Message passing . Supervisor patterns . Loops and conflicts
Module 06
Workflow Automation
Triggers and webhooks . Zapier . Scheduling . n8n . Make . Error queues
Lab
Email Triage Automation
Module 07
Business Integrations
Gmail and Outlook . Google Sheets . Databases . WhatsApp and Slack . Document generation
Module 08
Reliability and Deployment
Observability . Tracing . Evaluation . Rate limits . Sandboxing . Deployment
Assessment & certification
Module assignments and labs
25%
Final project and review
40%
Learners who complete all modules, submit the final project and clear the review receive a course completion certificate from Kaizen Infinities Private Limited. Project work is documented for the learner's portfolio, and interview preparation is included in the closing sessions.
Career outcomes . Roles this programme prepares for
AI Agent DeveloperAutomation EngineerAI Solutions EngineerRPA and AI ConsultantBackend AI Developer
