CrewAI Fundamentals Training in York, England

This course introduces CrewAI, a powerful framework designed for coordinating multiple autonomous AI agents (based on Large Language Models) to work collaboratively on complex workflows. Learners will gain an understanding of CrewAI’s architecture, its agent-crew-task structure, and how to design, build, and run multi-agent systems for real-world problem-solving.

Course Agenda:

Introduction to Multi-Agent AI and CrewAI

• What are AI agents and multi-agent systems?

• Evolution of CrewAI and its applications

• Use cases in automation, research, coding, finance, etc.

Setting Up CrewAI

• Installing CrewAI and dependencies

• Overview of LLMs supported (e.g., OpenAI, Anthropic, etc.)

• Basic configuration and environment setup

Core Concepts in CrewAI

• Agent, Crew, Role, Goal, and Task definitions

• Role-based prompt engineering

• Communication and task routing in agents

Building Agents and Crews

• Creating agents with custom goals and personalities

• Assigning roles and defining tools

• Assembling a crew and coordinating workflows

Orchestrating Tasks

• Defining single-step and multi-step tasks

• Handling task dependencies and outputs

• Executing and monitoring crew performance

Debugging and Optimization

• Logging and interpreting agent output

• Common errors and troubleshooting tips

• Performance optimization and scalability

Hands-on Exercises