AI CHATBOT SYSTEMS
& AUTOMATION
DESIGN, DEPLOY, AND OPERATE REAL-WORLD AI SYSTEMS.
Built to expose students to how AI chatbots actually work in production — not just how to prompt or demo them.
JOIN THIS COURSE NOWCourse Overview
This program introduces students to Artificial Intelligence, Generative AI, and Large Language Models through hands-on chatbot development and automation use cases.
Students learn how AI systems like ChatGPT function internally, how chatbots are integrated into real business workflows, and how organizations use AI to automate customer support, operations, and decision-making.
The focus is not on isolated tools, but on understanding systems, limitations, and real-world deployment challenges.
Tools & Enterprise Stack
You won’t just learn concepts. You’ll work inside the same platforms used to build, deploy, and operate real-world AI chatbot systems.
OpenAI
LLMs, embeddings, and real production API workflows
Claude
Safety-first LLMs and reasoning-oriented systems
Microsoft Azure
Enterprise AI deployment, Azure OpenAI & cloud services
AWS
Cloud fundamentals, compute, and scalable backends
Jira
Incident tracking, workflows, and production coordination
What You Will Build
AI & LLM Foundations
- • How LLMs work internally
- • Reasoning vs pattern matching
- • Behavior under ambiguity
Production Chatbot Design
- • 24/7 systems
- • Prompt reliability
- • Hallucination control
Automation & Integration
- • Workflow automation
- • Multi-platform deployment
- • System scalability
Enterprise Exposure
- • Cloud environments
- • Cost & latency tradeoffs
- • Production constraints
What You Leave With
Production-level AI system understanding
Hands-on chatbot deployment experience
Ability to reason about failures & tradeoffs
Industry-aligned system thinking
Meet Our Instructor
Pankaj Kharkwal
Founder, Pankh AI · Technology Advisor, Vybe Labs, Ex-Microsoft, Oracle & EY
Pankaj Kharkwal is a Generative AI and Large Language Model architect with industry experience building AI solutions for real-world business problems.
Having worked with organizations like Microsoft, Oracle, and EY, he focuses on teaching students how AI systems are actually used in production — not just how to experiment with them.