AI Agent Development Online Live Class by Experts
Our Training/Internship Process
AI Agent Development - Syllabus, Fees & Duration
Introduction to AI Agents
- What are AI Agents?
- Evolution of AI Agents
- Types of AI Agents
- AI Agent Architecture
Python for AI Development
- Python Fundamentals
- Virtual Environments
- API Integration
- JSON & File Handling
OpenAI API Development
- OpenAI Models
- Chat Completions API
- Responses API
- Function Calling
- Structured Outputs
Prompt Engineering
- Prompt Design
- Few-shot Prompting
- Chain of Thought
- Prompt Optimization
LangChain Essentials
- Prompt Templates
- Chains
- Memory
- Tools & Agents
LangGraph Development
- Graph-Based Workflows
- State Management
- Conditional Routing
- Human-in-the-Loop
- Agent Orchestration
Model Context Protocol (MCP)
- Introduction to MCP
- MCP Architecture
- MCP Clients & Servers
- Tool Integration
- Secure Context Sharing
RAG & Vector Databases
- Embeddings
- FAISS
- ChromaDB
- Semantic Search
- Document Retrieval
Multi-Agent Systems
- Agent Collaboration
- Task Delegation
- Supervisor Agents
- Workflow Automation
AI Agent Deployment
- FastAPI
- Docker
- Cloud Deployment
- Monitoring & Logging
Real-World Projects
- AI Customer Support Agent
- Document Intelligence Agent
- Research Assistant
- Coding Assistant
- Enterprise AI Agent
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
The AI Agent Development (OpenAI, LangGraph & MCP) course in Kimberley is a comprehensive 3-month program designed for students, developers, and IT professionals who want to build intelligent AI agents using the latest AI frameworks and tools. . Learn to develop autonomous AI agents with OpenAI APIs, LangGraph workflows, the Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), vector databases, and modern AI orchestration frameworks. By the end of the program, you will have the practical skills to design, develop, deploy, and integrate production-ready AI agents for enterprise and business applications in Kimberley.
Throughout the course, you will build real-world AI applications including AI assistants, customer support agents, document intelligence systems, research assistants, coding assistants, and multi-agent automation solutions. 
