Duration
40 Hours
2 parts × 20 hrs each
Fee
₹5,000/mo
Audience
Developers & Tech Professionals
Python basics recommended
Part 1
GenAI Systems
20 Hours — LLMs, Prompts, Embeddings, RAG
01Introduction to Generative AI
02GenAI use cases in real business applications
03Large Language Models overview
04Tokens and tokenization
05Context window and model limitations
06Temperature and model parameters
07Prompt engineering basics
08System prompts and role-based prompting
09Few-shot prompting and examples-based prompting
10Structured output and JSON response generation
11LLM API integration
12Model selection and comparison
13Embeddings
14Semantic search
15Vector databases
16Document ingestion
17PDF and text processing
18Chunking strategies
19Real Project: Document-based Q&A system using RAGProject
20Real Project: GenAI business assistant using LLM API and promptsProject
Part 2
Agentic AI Systems
20 Hours — Agents, Tool Calling, LangGraph, Workflows
01Introduction to Agentic AI
02Chatbot vs workflow vs AI agent
03Agentic AI use cases
04Tool calling
05Function calling
06API integration with agents
07Agent workflow design
08Single-step and multi-step agents
09Multi-step task execution
10Task planning and decision making
11Error handling and fallback flow
12LangGraph introduction
13Nodes and edges in LangGraph
14State management
15Conditional routing
16Tool execution using LangGraph
17Memory in AI agents
18Human-in-the-loop approval
19Real Project: AI agent with tool calling and API integrationProject
20Real Project: LangGraph-based multi-step business workflow agentProject
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