Become an Industry-Ready Generative AI for Developers
To empower learners to build AI-powered applications using generative models and LLMs (Large Language Models), applying prompt engineering, API integration, and model fine-tuning techniques.
- Academic partner with UGC, AICTE, and NCVET alignment
- 200+ programs across domains
- 1,000+ industry partners and global collaborations
Program Objective
To empower learners to build AI-powered applications using generative models and LLMs (Large Language Models), applying prompt engineering, API integration, and model fine-tuning techniques.
Key Features
Program Outcomes
Curriculum Structure
Module 1 - Generative AI Concepts & Model Architectures
Topics Covered:
Introduction to Generative AI
Evolution of AI: From ML to Generative Models
Large Language Models (LLMs) Overview
Transformers Architecture
Diffusion Models & GANs Basics
Text, Image, and Code Generation Models
Model Training Fundamentals
Module 2 - Prompt Engineering & Fine-Tuning
Topics Covered:
Fundamentals of Prompt Engineering
Zero-shot, One-shot & Few-shot Prompting
Chain-of-Thought Prompting
Role-based & Structured Prompts
Prompt Optimization Techniques
Fine-Tuning vs. Prompt Engineering
Introduction to LoRA & Parameter-Efficient Fine-Tuning
Module 3 - APIs & Frameworks for LLM Integration
Topics Covered:
Working with LLM APIs
REST API Basics for AI Integration
Introduction to LangChain
Vector Databases & Embeddings
Retrieval-Augmented Generation (RAG)
Integrating LLMs into Web Applications
Deployment Basics
Module 4 - Building Generative Applications (Text, Image, Code) Module 5 - Responsible AI & Model Governance
Topics Covered:
Building AI Chatbots
Text Summarization & Content Generation Apps
Image Generation Applications
AI Code Assistants
Multi-modal Applications
UI/UX Considerations for AI Apps
Performance Optimization
Module 5 - Responsible AI & Model Governance
Topics Covered:
AI Ethics & Bias
Data Privacy & Security
Hallucinations in LLMs
Model Explainability
Governance Frameworks
Risk Assessment & Mitigation
Regulatory Overview
Module 6 - Capstone Project: Generative AI Application
Topics Covered:
Problem Statement Selection
Project Planning & Architecture
Model Selection & Integration
Frontend + Backend Implementation
Testing & Validation
Deployment & Presentation
Documentation & Demo
Module 7 - Employability & Professional Skills
Topics Covered:
Resume Building for AI Roles
GitHub Portfolio Development
LinkedIn Optimization
Interview Preparation (Technical + HR)
Communication & Presentation Skills
Industry Case Studies
Career Pathways in Generative AI
Tools & Softwares
Salary Scale
Career Roles
- Generative AI Developer
- AI Application Engineer
- Prompt Engineer
- AI Automation Specialist
- LLM Integration Developer
FAQ's
Yes. You'll receive VTU-compliant certificates and documentation.
No. The program starts from fundamentals and scales gradually.
Prediction models, CNN-based classifiers, NLP applications, and a full ML pipeline.
Yes — resume, LinkedIn, GitHub, mock interviews & job guidance.
Offered in both offline and hybrid formats.
Yes, you will receive a verified completion certificate from Rooman Technologies upon meeting all requirements.
CSE, ISE, AIML, ECE, EEE, Civil, Mechanical and all final-year VTU students.
Python, Scikit-learn, TensorFlow, Pandas, Kaggle workflows, cloud ML basics.
Contact Us
Have questions about our programs or need guidance? Reach out to us and we’ll be happy to help.
Email Us
online@rooman.net
Call Us
080 6945 1000
Send us a Message
Contact Us
Have questions about our programs or need guidance? Reach out to us and we’ll be happy to help.
Email Us
online@rooman.net
Call Us
080 6945 1000