Module 1: Advanced Agentic AI Architectures
Agent lifecycle and autonomy levels
Deliberative, hybrid, and cognitive agents
Event-driven and goal-driven agents
Agent operating systems (Agent OS concepts)

Module 2: Multi-Agent Systems & Collaboration
Single-agent vs multi-agent complexity
Agent roles, delegation, and coordination
Communication protocols between agents
Swarm intelligence and consensus models

Module 3: Planning, Reasoning & Decision Engines
Long-horizon planning techniques
Task decomposition and prioritization
Self-reflection and critique loops
Reinforcement signals and adaptive behavior

Module 4: Tool Orchestration & Execution Control
Dynamic tool selection
API chaining and workflow automation
Error recovery and fallback strategies
Human-in-the-loop execution models

Module 5: Memory, Knowledge & Context Engineering
Hierarchical memory architectures
Vector databases and hybrid memory
Retrieval-Augmented Generation (RAG) for agents
Memory compression and relevance scoring

Module 6: Agentic AI for Enterprise Systems
Autonomous IT & DevOps agents
AI agents for data engineering and analytics
Business process and decision agents
Domain-specific agent frameworks

Module 7: Evaluation, Monitoring & Optimization
Agent performance metrics
Cost, latency, and scalability trade-offs
Logging, tracing, and observability
Prompt, tool, and memory optimization

Module 8: Security, Safety & Governance
Prompt injection and agent misuse
Access control and sandboxing
Guardrails, policy enforcement, and audits
Regulatory and compliance considerations

Module 9: Production Deployment & Scaling
Agent deployment patterns
Cloud and hybrid infrastructure for agents
Versioning, rollback, and updates
Agent lifecycle management

Module 10: Capstone Project & Case Studies
Designing a multi-agent system
Solving a complex real-world problem
Performance evaluation and risk analysis
Capstone presentation and review