This Generative AI project based course is designed to help you build real-world LLM applications end to end, using industry-leading models like LLaMA, Google Gemini, and OpenAI GPT.. Instead of focusing on theory alone, this course follows a hands-on, practical approach, where you will design, develop, and deploy 3 production-style GenAI projects that mirror real industry use cases. By the end of this course, you will have a strong Generative AI project portfolio, real experience working with LLM APIs, RAG systems, and vector databases, and a clear understanding of how modern AI-powered products are built and deployed in real-world environments.
What You Will Build (Real-World Projects) :
Project 1 : Cold Email Generator using LLaMA 3.3
Build an AI-powered cold email generator that:
- Analyzes job descriptions or business requirements
- Extracts relevant skills and context
- Automatically generates personalized, high-quality cold emails
This project demonstrates how companies use open-source LLMs like LLaMA for sales automation and outreach.
Project 2 : Text-to-SQL Generator using Google Gemini
Create an intelligent system that:
- Converts natural language questions into SQL queries
- Works on real database schemas
- Enables non-technical users to query databases using plain English
This project reflects real enterprise use cases in data analytics, business intelligence (BI), and AI-driven decision-making systems.
Project 3 : Food Calorie Detector using OpenAI GPT
Develop a multimodal AI pipeline that:
- Takes food images as input
- Extracts food information using vision models
- Retrieves verified nutritional data
- Generates structured calorie, protein, fat, and carb insights using GPT
This project showcases end-to-end GenAI workflows, combining computer vision, retrieval-augmented generation (RAG), and LLM reasoning.
