Multi-Agent AI Systems Development Certified Course

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About Course

The Multi-Agent AI Systems Development Certified Course is an industry-focused program designed to teach learners how to design, develop, orchestrate, deploy, and manage intelligent multi-agent systems where multiple AI agents collaborate to solve complex tasks. The course covers agent architecture, LLM integration, prompt engineering, agent memory, tool and API calling, task delegation, inter-agent communication, workflow orchestration, RAG, agent evaluation, observability, security, and production deployment. Learners gain hands-on experience with modern frameworks such as LangGraph, LangChain, CrewAI, AutoGen, OpenAI Agent SDK, and vector databases, while building real-world multi-agent applications for automation, research, customer support, data analysis, software development, and enterprise workflows.

Key Features of Course Divine:

  • Collaboration with E‑Cell IIT Tirupati
  • 1:1 Online Mentorship Platform
  • Credit-Based Certification
  • Live Classes Led by Industry Experts
  • Live, Real-World Projects
  • 100% Placement Support
  • Potential Interview Training
  • Resume-Building Activities

CAREER OPPORTUNITIES AFTER Multi-Agent AI Systems Development:

  • Multi-Agent AI Engineer
  • AI Agent Developer
  • Generative AI Engineer
  • AI/ML Engineer
  • LLM Application Engineer
  • AI Automation Engineer
  • Multi-Agent Systems Architect
  • AI Solutions Engineer
  • Conversational AI Engineer
  • AI Workflow Engineer
  • AgentOps Engineer
  • LLMOps Engineer
  • AI Platform Engineer
  • Intelligent Automation Specialist
  • AI Solutions Architect

ESSENTIAL SKILLS YOU WILL DEVELOP – Multi-Agent AI Systems Development:

  • Multi-Agent System Architecture & Design
  • AI Agent Development & Orchestration
  • LLM Integration & Prompt Engineering
  • Agent Communication & Collaboration
  • Task Planning, Delegation & Coordination
  • Tool Calling & API Integration
  • Agent Memory & Context Management
  • RAG & Knowledge Retrieval
  • Multi-Agent Workflow Automation
  • Agent Evaluation & Performance Testing
  • AI Agent Monitoring & Observability
  • Security, Guardrails & Access Control
  • Error Handling & Agent Reliability
  • AI Application Deployment & Scaling
  • Production Multi-Agent System Optimization

Tools Covered:

  • LangChain & LangGraph
  • CrewAI
  • AutoGen
  • OpenAI Agent SDK
  • LlamaIndex
  • Microsoft Semantic Kernel
  • Hugging Face
  • FastAPI
  • Pinecone / Chroma / FAISS
  • Docker & Kubernetes
  • Git & GitHub Actions
  • LangSmith
  • OpenTelemetry
  • MLflow
  • AWS / Azure / Google Cloud

Syllabus:

Module 1: Multi-Agent AI Fundamentals

  • Multi-Agent Systems Architecture & Core Concepts
  • LLMs, AI Agents & Agentic Workflows
  • Single-Agent vs. Multi-Agent Systems

Module 2: AI Agent Development

  • Agent Planning, Reasoning & Decision-Making
  • Tool Calling, Function Calling & API Integration
  • Agent Memory & Context Management

Module 3: Multi-Agent Architecture & Design

  • Agent Roles, Responsibilities & Coordination
  • Task Delegation & Workflow Management
  • Agent Communication & Collaboration Patterns

Module 4: LangChain & LangGraph

  • LangChain Agent Development
  • LangGraph State-Based Workflows
  • Building Multi-Agent Graph Architectures

Module 5: CrewAI & AutoGen

  • CrewAI Agents, Crews & Tasks
  • AutoGen Conversational Agent Workflows
  • Multi-Agent Collaboration & Orchestration

Module 6: RAG & Knowledge-Based Agents

  • RAG Architecture & Document Processing
  • Vector Databases & Semantic Search
  • Knowledge Retrieval for Multi-Agent Systems

Module 7: Advanced Multi-Agent Workflows

  • Sequential, Parallel & Hierarchical Agents
  • Human-in-the-Loop Workflows
  • Complex Task Planning & Agent Coordination

Module 8: Agent Evaluation & Observability

  • Agent Testing & Performance Evaluation
  • Logging, Tracing & Workflow Monitoring
  • Debugging Agent Failures & Hallucinations

Module 9: Security & Production Deployment

  • Agent Security, Guardrails & Access Control
  • Docker, APIs & Cloud Deployment
  • Scalability, Reliability & Error Handling

Module 10: Real-World Multi-Agent Projects

  • Enterprise Multi-Agent Automation System
  • AI Research & Data Analysis Agent Team
  • End-to-End Production Multi-Agent Application

Industry Projects:

  • Multi-Agent Customer Support Automation System
  • AI Research & Information Analysis Agent Team
  • Multi-Agent Software Development Assistant
  • Intelligent Business Process Automation System
  • AI-Powered Data Analysis Agent Team
  • Multi-Agent RAG Knowledge Management System
  • Autonomous IT Helpdesk Multi-Agent System
  • AI Sales & Lead Qualification Agent System
  • Multi-Agent Content Research & Generation Platform
  • Enterprise Multi-Agent Workflow Orchestration System

Who is this program for?

  • AI/ML Engineers and Generative AI Professionals
  • AI Agent & Multi-Agent System Developers
  • Software Developers and Full-Stack Developers
  • LLM Application Engineers
  • Data Scientists and Data Engineers
  • MLOps, LLMOps & AgentOps Engineers
  • DevOps and Cloud Engineers
  • AI Automation and Workflow Engineers
  • AI Solutions Architects and Technical Leads
  • IT Professionals transitioning into Agentic AI
  • Students and Freshers interested in Multi-Agent AI Technologies

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com

🌍 International Students (USD Payments Only)

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  • Full Name
  • Course Name
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Email: info@coursedivine.com
WhatsApp: +91 9100348679.

 
 
 
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