Generative AI
Build real applications with large language models, prompt engineering, LangChain, RAG and vector databases.
What your team will learn
LLMs & Prompt Engineering
Master advanced prompting techniques to elicit high-quality, accurate responses from popular Large Language Models.
RAG & Vector Databases
Build intelligent systems that query private enterprise data using Pinecone, FAISS, and vector search techniques.
AI Application Development
Develop full-stack AI applications using Python frameworks like LangChain, FastAPI, and Flask.
AI APIs Integration
Integrate robust AI capabilities using OpenAI, Claude, and Hugging Face APIs into modern applications.
Machine & Deep Learning
Understand the core mathematical foundations, neural networks, and algorithms that power modern AI.
MLOps & Deployment
Deploy scalable AI models and applications using Docker, AWS, and Azure cloud infrastructure.
Program curriculum
15 modules. Modules and depth can be customised for your team.
01Introduction to Artificial Intelligence
- AI Fundamentals
- AI Ecosystem
- Introduction to Generative AI
02Python for AI Development
- Python Fundamentals
- Advanced Python
- Python Libraries
03Machine Learning Fundamentals
- ML Basics
- ML Algorithms
- Model Evaluation
04Deep Learning Fundamentals
- Neural Networks
- Deep Learning Frameworks
- CNN & RNN Overview
05Introduction to Large Language Models
- LLM Fundamentals
- Popular LLMs
- LLM Applications
06Prompt Engineering
- Prompt Engineering Basics
- Advanced Prompting Techniques
- AI Productivity
07OpenAI & LLM APIs
- OpenAI API
- AI Application Development
- Cost Optimization
08LangChain Framework
- LangChain Fundamentals
- LangChain Components
- AI Workflow Automation
09Retrieval-Augmented Generation
- RAG Fundamentals
- Vector Databases
- RAG Applications
10AI Agents & Automation
- AI Agents
- AI Automation
- AI Tools Integration
11Full Stack AI Application Development
- Frontend for AI Apps
- Backend APIs
- AI Integration
12AI Deployment & MLOps
- AI Model Deployment
- AWS AI Services
- MLOps Basics
13AI Ethics & Security
- Responsible AI
- AI Security
- AI Governance
14Real-Time Generative AI Projects
- Major Projects
15AI Tools Covered
- AI Platforms
- AI Frameworks
- Vector Databases
- Deployment Tools
Tools & technologies covered
Who should attend
Frequently asked questions
What is Generative AI and why is it important in 2026?
Generative AI is a subset of artificial intelligence capable of creating new content (text, code, images, etc.) from learned data patterns. In 2026, it is the most critical driver of enterprise automation, enabling companies to build intelligent applications that solve complex problems, drastically increasing the market demand for skilled AI developers.
What projects will I build during the course?
You will build several major real-world projects, including a custom Chatbot using OpenAI API, an intelligent document Q&A system using RAG and Vector Databases, an automated content generation pipeline, and a full-stack AI application deployed to the cloud.
Can this program be customised for our team?
Yes. We tailor the modules, depth, examples and hands-on projects to your team's current skills, technology stack and business goals.
Where is the training delivered?
On-site at your office or campus, live online for distributed teams, or at our training centre in Nagole, Hyderabad, whichever suits your team best.
How long does the program take?
Duration depends on the modules you choose and your team's availability. Our training proposal includes a detailed schedule with hours, timeline and session plan.
Do participants receive a certificate?
Yes. Participants who complete the program receive a PRR Technologies training completion certificate.
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View programTrain your team in Generative AI
Tell us your team size, current skill level and preferred format. We will send a tailored training proposal.