Highlights
Curriculum &
Faculty
Admissions
& Fees
Career
Prospects
Applied AI Chatbot Challenge
Build AI chatbots that solve real-world problems and improve processes. Examples include:
Create advanced AI chatbots that solve one meaningful use case by combining Python, LLM APIs, and no-code tools.
Build a wellbeing chatbot using basic psychological principles to help users manage stress & anxiety.
Create a study buddy chatbot to assist students with subject knowledge and doubt solving.
Design a customer support chatbot for handling FAQs and product queries.
Agentic AI Accelerator for Business
Build autonomous, tool-using AI agents that automate org workflows and integrate with live data sources.
Develop AI agents that reduce man hours and boost team productivity. Examples include:
Automate HR Operations (onboarding, payroll, leave management) for a large IT consulting firm.
Generate ad creatives and design variants for digital marketing for an online D2C brand.
Automate procurement across 100+ products for an automotive manufacturing plant.
AI Application in Industry:
ML Consulting Garage
Transform business data into actionable insights using supervised and unsupervised ML.
Create actionable insights backed by data to solve a company-specific problem. Examples include:
Use clustering algorithms to segment customers for companies like Myntra or Zomato.
Build a churn-prediction model for a subscription business to identify high-risk customers.
Develop a sales-prediction model for an e-commerce brand to optimise marketing spend.
RAG System Building Challenge
Build powerful, domain-specific AI assistants using Retrieval-Augmented Generation (RAG) that deliver accurate, traceable answers on top of private data.
Deploy a RAG system that answers 1,000+ product-specific customer queries without human intervention. Examples:
Design a legal document summariser to assist lawyers with case preparation.
Build a medical assistant to support doctors in diagnostics and second opinions.
Create an educational assistant to support researchers in their thesis development.
AI Immersion in Retail, Health, and Finance
Build and deploy domain-specific AI solutions that are reliable, compliant, and market-ready.
Design industry-ready AI solutions and secure 3–5 real paying clients. Examples include:
Create a system that automates supplier selection and inventory management for a retailer.
Develop an AI system for early disease diagnosis (e.g., cancer risk) through medical record analysis.
Build a reinforcement learning–based portfolio optimisation system to balance risk and return.
PROFESSIONAL GUIDANCE
