50000 +
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(500)
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16 Weeks
Duration
Our Alumni Work at Top Companies
AI Agents Course Curriculum
It stretches your mind, think better and create even better.
Topics:
Duration: 2 Weeks
1.1 Agent Fundamentals
Week 1: Core Concepts
Understanding Agents
What Makes a System an “Agent”?
Agents vs. Traditional AI Systems
History and Evolution of Agent Systems
Current State of Agent Technology
Types of Agents
Simple Reflex Agents
Model-Based Reflex Agents
Goal-Based Agents
Utility-Based Agents
Learning Agents
Hybrid Agent Architectures
Agent Components
Perception Module: Sensing the Environment
Knowledge Base: Information Storage
Reasoning Engine: Logic and Inference
Planning Module: Goal Achievement
Action Module: Execution and Control
Learning Module: Adaptation and Improvement
Agent Environments
Fully vs. Partially Observable
Deterministic vs. Stochastic
Episodic vs. Sequential
Static vs. Dynamic
Discrete vs. Continuous
Single vs. Multi-agent
1.2 Cognitive Architecture
Week 2: Agent Intelligence
Knowledge Representation
Symbolic Representations
Semantic Networks
Frames and Scripts
Ontologies
Knowledge Graphs
Memory Systems
Working Memory Architecture
Long-term Memory Storage
Episodic Memory
Semantic Memory
Procedural Memory
Memory Retrieval Mechanisms
Perception and Understanding
Natural Language Understanding
Computer Vision Integration
Speech Recognition
Multimodal Perception
Context Awareness
Lab Project: Build a basic reflex agent with perception and action capabilities
Topics:
Duration: 2 Weeks
2.1 Architectural Designs
Week 1: Core Architectures
BDI Architecture
Beliefs: Information State
Desires: Goals and Objectives
Intentions: Committed Plans
BDI Reasoning Cycle
Implementation Strategies
Layered Architectures
Reactive Layer
Deliberative Layer
Social Layer
Subsumption Architecture
InteRRaP Architecture
Blackboard Systems
Blackboard Data Structure
Knowledge Sources
Control Components
Collaborative Problem Solving
Cognitive Architectures
SOAR Architecture
ACT-R Framework
CLARION System
Sigma Architecture
2.2 Modern Agent Patterns
Week 2: Contemporary Designs
LLM-Based Agents
Prompt-Based Reasoning
Chain-of-Thought Agents
ReAct Pattern
Reflexion Architecture
Tool-Augmented Agents
Hybrid Architectures
Combining Symbolic and Neural
Neuro-Symbolic Integration
Hierarchical Agent Designs
Modular Agent Systems
Specialized Patterns
Conversational Agents
Task-Oriented Agents
Information Retrieval Agents
Monitoring Agents
Autonomous Software Agents
Project: Design and implement a BDI agent for task automation
Topics:
Duration: 2 Weeks
3.1 LangChain Fundamentals
Week 1: Core Framework
LangChain Architecture
Chains and Sequential Processing
Agents and Tools
Memory Systems
Callbacks and Events
Output Parsers
Agent Types in LangChain
Zero-shot ReAct
Conversational ReAct
Self-ask with Search
Plan-and-Execute
OpenAI Functions Agent
XML Agent
Tool Integration
Built-in Tools
Custom Tool Development
Tool Selection Strategies
Error Handling
Tool Chaining
Memory Management
Conversation Buffer Memory
Summary Memory
Entity Memory
Knowledge Graph Memory
Vector Store Memory
3.2 Advanced LangChain
Week 2: Complex Agent Systems
Custom Agents
Agent Executor Customization
Custom Prompt Templates
Dynamic Tool Selection
Multi-step Reasoning
Agent Evaluation
Advanced Patterns
Hierarchical Agents
Multi-Agent Conversations
Agent Supervisors
Autonomous Agents
Self-Improving Agents
Integration Capabilities
API Integration
Database Connections
Vector Stores
External Services
Webhook Support
Production Features
Streaming Responses
Async Operations
Caching Strategies
Token Management
Cost Optimization
Lab: Build a complex agent system using LangChain
Topics:
Duration: 2 Weeks
4.1 Graph-Based Agent Design
Week 1: LangGraph Fundamentals
Graph Architecture
Nodes and Edges
State Management
Conditional Routing
Cycles and Loops
Parallel Execution
Building Stateful Agents
State Definition
State Transitions
Checkpointing
Persistence Layers
State Recovery
Control Flow
Sequential Execution
Conditional Branching
Parallel Processing
Loop Handling
Error States
Memory and Context
State Channels
Shared Memory
Context Propagation
Memory Persistence
Distributed State
4.2 Advanced LangGraph Patterns
Week 2: Complex Workflows
Multi-Agent Graphs
Agent Nodes
Communication Channels
Coordination Patterns
Consensus Mechanisms
Distributed Execution
Human-in-the-Loop
Approval Workflows
Feedback Integration
Interactive Agents
Escalation Patterns
Quality Control
Advanced Features
Streaming in Graphs
Real-time Updates
Graph Visualization
Performance Optimization
Debugging Tools
Production Deployment
Graph Serialization
Distributed Graphs
Fault Tolerance
Monitoring Integration
Version Control
Project: Develop a stateful multi-agent system with LangGraph
Topics:
Duration: 2 Weeks
5.1 CrewAI Fundamentals
Week 1: Building Agent Crews
Crew Components
Agent Definition
Role Assignment
Goal Setting
Backstory Creation
Tool Assignment
Task Management
Task Definition
Task Dependencies
Task Assignment
Sequential Tasks
Parallel Tasks
Crew Orchestration
Process Types
Execution Flow
Agent Collaboration
Resource Sharing
Result Aggregation
Built-in Capabilities
Web Search
File Operations
Code Execution
API Calls
Custom Tools
5.2 Advanced CrewAI
Week 2: Complex Crew Systems
Advanced Patterns
Hierarchical Crews
Dynamic Agent Creation
Adaptive Workflows
Self-Organizing Teams
Emergent Behaviors
Optimization Strategies
Performance Tuning
Resource Management
Cost Optimization
Parallel Processing
Caching Mechanisms
Integration and Extension
Custom Agent Types
External Tool Integration
Memory Systems
Callback Handlers
Event Processing
Production Features
Crew Monitoring
Error Recovery
Logging Systems
Metrics Collection
Deployment Strategies
Lab: Build an autonomous research crew with specialized agents
Topics:
Duration: 1 Week
6.1 Microsoft AutoGen
Core Concepts
Conversable Agents
User Proxy Agents
Assistant Agents
Group Chat Manager
Code Execution
Agent Conversations
Multi-turn Dialogues
Agent Negotiations
Collaborative Problem Solving
Code Generation and Execution
Human Feedback Integration
Advanced Features
Custom Agent Types
Function Calling
Context Management
Conversation Patterns
Teachable Agents
6.2 MCP (Model Context Protocol)
Protocol Architecture
Server Components
Client Integration
Resource Management
Tool Definitions
Context Windows
Implementation
Building MCP Servers
Client Development
Protocol Extensions
Security Considerations
Performance Optimization
Project: Implement a multi-agent system using AutoGen with MCP integration
Topics:
Duration: 2 Weeks
7.1 Reasoning Strategies
Week 1: Core Reasoning
Logic-Based Reasoning
Propositional Logic
First-Order Logic
Description Logic
Temporal Logic
Fuzzy Logic
Probabilistic Reasoning
Bayesian Networks
Markov Decision Processes
Hidden Markov Models
Monte Carlo Methods
Belief Propagation
Case-Based Reasoning
Case Representation
Similarity Metrics
Case Retrieval
Adaptation Strategies
Case Retention
Analogical Reasoning
Structure Mapping
Analogical Transfer
Cross-Domain Reasoning
Creative Problem Solving
7.2 LLM-Based Reasoning
Week 2: Neural Reasoning
Prompt-Based Reasoning
Chain-of-Thought (CoT)
Tree-of-Thoughts (ToT)
Graph-of-Thoughts (GoT)
Self-Consistency
Least-to-Most Prompting
Advanced Techniques
ReAct Framework
Reflexion Method
Self-Ask Approach
Decomposed Prompting
Recursive Reasoning
Hybrid Approaches
Neuro-Symbolic Reasoning
Program-Aided Reasoning
Tool-Augmented Reasoning
Multi-Modal Reasoning
Meta-Reasoning
Reasoning Validation
Fact Checking
Consistency Verification
Logic Validation
Confidence Scoring
Explanation Generation
Lab: Implement advanced reasoning chains for complex problem solving
Topics:
Duration: 2 Weeks
8.1 Planning Algorithms
Week 1: Classical Planning
Search-Based Planning
State Space Search
A* Algorithm
Breadth-First Search
Depth-First Search
Iterative Deepening
Hierarchical Planning
Task Decomposition
HTN Planning
Goal Decomposition
Abstract Planning
Refinement Planning
Temporal Planning
Timeline Representation
Temporal Constraints
Scheduling Algorithms
Resource Management
Concurrent Actions
Partial-Order Planning
Plan Space Search
Causal Links
Threat Resolution
Plan Refinement
Constraint Satisfaction
8.2 Advanced Planning
Week 2: Modern Approaches
Learning-Based Planning
Reinforcement Learning
Model-Based RL
Imitation Learning
Inverse RL
Meta-Learning
LLM Planning
Natural Language Plans
Code Generation Planning
Tool Use Planning
Multi-Step Planning
Plan Verification
Uncertainty Handling
Contingency Planning
Probabilistic Planning
Robust Planning
Adaptive Planning
Replanning Strategies
Multi-Objective Planning
Goal Prioritization
Trade-off Analysis
Pareto Optimization
Constraint Handling
Resource Optimization
Project: Build an autonomous planning agent for complex task execution
Topics:
Duration: 2 Weeks
9.1 Communication and Coordination
Week 1: Agent Communication
Communication Protocols
Message Passing
Broadcast Communication
Point-to-Point
Publish-Subscribe
Blackboard Systems
Communication Languages
FIPA-ACL
KQML
Custom Protocols
Natural Language
Semantic Communication
Coordination Mechanisms
Contract Net Protocol
Auction Mechanisms
Voting Systems
Consensus Protocols
Market-Based Coordination
Synchronization
Time Synchronization
Action Synchronization
State Synchronization
Distributed Locks
Barrier Synchronization
9.2 Collaborative Intelligence
Week 2: Team Dynamics
Team Formation
Dynamic Team Building
Role Assignment
Capability Matching
Coalition Formation
Team Dissolution
Collaborative Problem Solving
Task Allocation
Load Balancing
Resource Sharing
Joint Planning
Collective Decision Making
Conflict Resolution
Negotiation Strategies
Mediation Mechanisms
Priority Systems
Compromise Algorithms
Arbitration Protocols
Emergent Behaviors
Swarm Intelligence
Self-Organization
Collective Learning
Adaptation Mechanisms
Evolution Strategies
Lab: Develop a multi-agent system for distributed problem solving
Topics:
Duration: 1 Week
10.1 Game-Theoretic Foundations
Basic Concepts
Nash Equilibrium
Dominant Strategies
Pareto Optimality
Zero-Sum Games
Cooperative Games
Strategic Reasoning
Opponent Modeling
Strategy Selection
Equilibrium Computation
Best Response
Mixed Strategies
Mechanism Design
Incentive Compatibility
Auction Design
Voting Mechanisms
Resource Allocation
Fair Division
10.2 Applications
Competitive Agents
Trading Agents
Negotiation Agents
Bidding Strategies
Market Making
Portfolio Management
Cooperative Agents
Coalition Games
Shapley Value
Core Solutions
Bargaining Solutions
Social Choice
Project: Build strategic agents for multi-agent negotiation
Topics:
Duration: 2 Weeks
11.1 Development Environment
Week 1: Tools and Frameworks
IDE and Debugging
VS Code Extensions
Debugging Tools
Profiling Tools
Testing Frameworks
Logging Systems
Agent Testing
Unit Testing Agents
Integration Testing
Behavior Testing
Performance Testing
Stress Testing
Simulation Environments
Agent Simulators
Virtual Environments
Scenario Generation
A/B Testing
Monte Carlo Simulation
Monitoring Tools
Agent Observability
Trace Analysis
Metric Collection
Log Aggregation
Visualization Dashboards
11.2 Agent Evaluation
Week 2: Quality Assurance
Performance Metrics
Response Time
Throughput
Resource Utilization
Success Rate
Error Rate
Behavioral Metrics
Goal Achievement
Task Completion
Decision Quality
Learning Rate
Adaptation Speed
Quality Metrics
Accuracy
Consistency
Robustness
Explainability
Trustworthiness
Benchmarking
Standard Benchmarks
Custom Benchmarks
Comparative Analysis
Performance Baselines
Regression Testing
Lab: Build a comprehensive testing suite for agent systems
Topics:
Duration: 1 Week
12.1 Agent Security
Security Threats
Adversarial Attacks
Data Poisoning
Model Extraction
Privacy Breaches
Unauthorized Access
Security Measures
Authentication Systems
Authorization Controls
Encryption Methods
Secure Communication
Audit Logging
Prompt Security
Injection Prevention
Input Validation
Output Sanitization
Context Isolation
Rate Limiting
12.2 Safety and Alignment
Safety Considerations
Goal Misalignment
Reward Hacking
Unintended Consequences
Capability Control
Emergency Stops
Alignment Techniques
Value Learning
Preference Learning
Constitutional AI
Interpretability
Human Oversight
Ethical Guidelines
Fairness Metrics
Bias Detection
Transparency Requirements
Accountability Measures
Privacy Protection
Project: Implement security and safety measures for production agents
Topics:
Duration: 2 Weeks
13.1 Deployment Strategies
Week 1: Infrastructure
Containerization
Docker Containers
Container Orchestration
Kubernetes Deployment
Service Mesh
Container Security
Cloud Deployment
AWS Services
Azure Solutions
GCP Platform
Serverless Agents
Edge Deployment
API Development
RESTful APIs
GraphQL APIs
WebSocket Support
gRPC Services
API Gateway
Database Integration
SQL Databases
NoSQL Solutions
Vector Databases
Graph Databases
Time-Series DB
13.2 Scalability and Performance
Week 2: Production Optimization
Scaling Strategies
Horizontal Scaling
Vertical Scaling
Auto-scaling
Load Balancing
Circuit Breakers
Performance Optimization
Caching Strategies
Query Optimization
Resource Pooling
Async Processing
Batch Processing
Distributed Systems
Microservices Architecture
Event-Driven Design
Message Queues
Stream Processing
Distributed Tracing
Cost Management
Resource Optimization
Cost Monitoring
Budget Controls
Spot Instances
Reserved Capacity
Lab: Deploy a production-ready agent system with auto-scaling
Topics:
Duration: 1 Week
14.1 Business Systems Integration
Enterprise Platforms
CRM Integration
ERP Systems
Business Intelligence
Workflow Automation
Document Management
Communication Channels
Email Integration
Slack/Teams Bots
SMS/WhatsApp
Voice Assistants
Web Widgets
Data Integration
ETL Pipelines
Real-time Sync
Batch Processing
Change Data Capture
API Integration
14.2 Compliance and Governance
Regulatory Compliance
GDPR Requirements
HIPAA Compliance
SOC 2 Standards
ISO Certifications
Industry Regulations
Governance Framework
Policy Management
Access Controls
Audit Trails
Version Control
Change Management
Documentation
Technical Documentation
User Guides
API Documentation
Compliance Reports
Operational Runbooks
Project: Integrate an agent system with enterprise platforms
TOOlS & PLATFORMS
Our AI Programs
Build a complete multi-agent customer service system with: - Natural language understanding - Intent recognition and routing - Knowledge base integration - Escalation handling - Sentiment analysis - Performance monitoring
Develop an AI research agent capable of: - Literature review automation - Data collection and analysis - Report generation - Citation management - Collaborative research - Quality validation
Create an agent system for business process automation: - Workflow orchestration - Document processing - Decision automation - Integration with enterprise systems - Compliance checking - Performance optimization
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