Agentic AI with CrewAI

The course Agentic AI with CrewAI from SpiralTrain teaches you how to build sophisticated multi-agent AI systems using the CrewAI framework.

CrewAI Fundamentals

The course Agentic AI with CrewAI begins with an overview of CrewAI and multi-agent concepts. Installation, core components, agent basics, crew structure, task fundamentals, process types, and sequential workflows are explored.

Agent Design

This module covers designing effective agents including defining roles, goals, backstories, creating specialized agents, delegation strategies, autonomy levels, agent memory, personality design, communication styles, and agent development best practices.

Tasks and Workflows

Here participants learn task definition including descriptions, expected outputs, dependencies, context management, callbacks, error handling, validation, asynchronous tasks, and optimization strategies for efficient workflow execution.

Tools Integration

This part focuses on integrating tools including built-in tools, custom tool creation, API integration, search capabilities, file operations, database access, web scraping, code execution, error handling, and tool best practices.

Advanced Orchestration

Advanced orchestration patterns are addressed including hierarchical processes, manager agents, conditional workflows, parallel execution, dynamic crew building, agent handoffs, workflow branching, optimization, and complex orchestration patterns.

Memory Systems

Memory management is explored covering short-term and long-term memory, entity memory, conversation history, storage solutions, retrieval strategies, context management, optimization, shared knowledge systems, and state persistence.

Production Deployment

Deployment considerations include strategies, environment configuration, API development, monitoring, logging, error recovery, performance optimization, cost management, security, testing strategies, and production deployment checklists.

Real-World Applications

Practical applications are covered including research automation, content generation, data analysis, customer service, marketing campaigns, business intelligence, process automation, decision support systems, industry-specific solutions, and case studies.

Advanced Topics

The course concludes with advanced subjects including human-in-the-loop systems, guardrails implementation, quality assurance, agent evaluation, prompt optimization, LLM integration, CrewAI ecosystem, troubleshooting, future trends, and capstone project.

Audience Course Agentic AI with CrewAI

This course is intended for AI developers, software engineers, and data scientists who want to build multi-agent AI systems using CrewAI.

Prerequisites Course Agentic AI with CrewAI

Participants should know Python programming and understand of AI and LLM concepts. Familiarity with prompt engineering and API integration is beneficial.

Realization Training Agentic AI with CrewAI

The training combines theoretical instruction with hands-on labs guided by a trainer. Participants build real multi-agent systems throughout the course.

Agentic AI with CrewAI Certificate

After successful completion, participants receive a certificate of participation in Agentic AI with CrewAI.

Modules

Module 1: CrewAI Fundamentals

• CrewAI Overview
• Multi-Agent Concepts
• Installation and Setup
• Core Components
• Agent Basics
• Crew Structure
• Task Fundamentals
• Process Types
• Sequential Workflows
• Best Practices

Module 2: Agent Design

• Agent Roles
• Agent Goals
• Agent Backstory
• Specialized Agents
• Agent Delegation
• Autonomy Levels
• Agent Memory
• Agent Personality
• Communication Styles
• Agent Best Practices

Module 3: Tasks and Workflows

• Task Definition
• Task Description
• Expected Output
• Task Dependencies
• Task Context
• Task Callbacks
• Error Handling
• Task Validation
• Async Tasks
• Task Optimization

Module 4: Tools Integration

• Built-in Tools
• Custom Tool Creation
• API Integration
• Search Tools
• File Operations
• Database Access
• Web Scraping
• Code Execution
• Tool Error Handling
• Tool Best Practices

Module 5: Advanced Orchestration

• Hierarchical Process
• Manager Agents
• Conditional Workflows
• Parallel Execution
• Dynamic Crew Building
• Agent Handoffs
• Workflow Branching
• Process Optimization
• Complex Orchestration
• Workflow Patterns

Module 6: Memory Systems

• Short-Term Memory
• Long-Term Memory
• Entity Memory
• Conversation History
• Memory Storage
• Memory Retrieval
• Context Management
• Memory Optimization
• Shared Knowledge
• State Persistence

Module 7: Production Deployment

• Deployment Strategies
• Environment Configuration
• API Development
• Monitoring and Logging
• Error Recovery
• Performance Optimization
• Cost Management
• Security Considerations
• Testing Strategies
• Production Checklist

Module 8: Real-World Applications

• Research Automation
• Content Generation
• Data Analysis
• Customer Service
• Marketing Campaigns
• Business Intelligence
• Process Automation
• Decision Support
• Industry Solutions
• Case Studies

Module 9: Advanced Topics

• Human-in-the-Loop
• Guardrails Implementation
• Quality Assurance
• Agent Evaluation
• Prompt Optimization
• LLM Integration
• CrewAI Ecosystem
• Troubleshooting
• Future Trends
• Capstone Project