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 Stuttgart 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 Stuttgart.
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. 
