Generative AI & LLM Development Online Live Class by Experts
Our Training/Internship Process
Generative AI & LLM Development - Syllabus, Fees & Duration
Introduction to Generative AI
- What is Generative AI?
- Applications of Generative AI
- Evolution of AI Models
- AI Ethics and Responsible AI
Large Language Models (LLMs)
- Introduction to LLMs
- Transformer Architecture
- Tokens and Embeddings
- Popular LLMs (GPT, Llama, Gemini, Claude)
Prompt Engineering
- Prompt Design
- Few-shot & Zero-shot Prompting
- Chain of Thought Prompting
- Role Prompting
Python for AI Development
- Python Basics
- Virtual Environment
- API Integration
- JSON Handling
OpenAI API Development
- OpenAI API
- Chat Completion API
- Function Calling
- Streaming Responses
Hugging Face Models
- Transformers Library
- Pipelines
- Model Hub
- Inference API
LangChain Framework
- Chains
- Prompt Templates
- Memory
- Agents
Vector Databases
- Embeddings
- FAISS
- ChromaDB
- Pinecone Basics
Retrieval-Augmented Generation (RAG)
- Document Loading
- Chunking
- Embedding Documents
- Semantic Search
AI Agents
- Autonomous AI Agents
- Tool Calling
- Task Automation
- Multi-Agent Systems
Building AI Applications
- AI Chatbots
- Document Q&A Systems
- Content Generation
- AI Assistants
Deployment
- Streamlit
- FastAPI
- Docker Basics
- Cloud Deployment
Final Projects
- AI Customer Support Chatbot
- PDF Question Answering System
- AI Resume Analyzer
- Enterprise Knowledge Assistant
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 1000 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
Course Highlights
This hands-on program covers Prompt Engineering, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Vector Databases, LangChain, Hugging Face, OpenAI APIs, and AI application deployment.
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Throughout the course, learners will gain practical experience by developing real-world AI solutions such as AI chatbots, document question-answering systems, AI assistants, content generators, resume analyzers, and workflow automation tools. By the end of the program, participants will have the skills required to design, build, and deploy modern AI applications, preparing them for high-demand careers in Generative AI and LLM development in **Nice**. The **Generative AI & LLM Development** course in **Nice** is designed for students, software developers, IT professionals, and AI enthusiasts who want to build intelligent AI-powered applications using the latest Generative AI technologies. 
