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Il y a 4 modules dans ce cours
This program introduces you to Building Your First Agent with CrewAI, designed for developers and AI enthusiasts who want to design and implement intelligent multi-agent systems. You will begin by learning the foundational concepts of AI agents and agentic AI, exploring how autonomous agents reason, collaborate, and execute tasks. The course also introduces the CrewAI framework, explaining its architecture and how agents, tasks, crews, and flows work together to automate complex workflows.
Next, you will explore LLM configuration and agent design techniques, including selecting suitable language models for different agent roles and applying effective prompt engineering strategies. You will learn how structured prompts guide agent behavior and improve reasoning quality. The course also covers context engineering, helping you design meaningful contextual inputs that allow agents to make better decisions and perform tasks more effectively.
As you progress, you will learn how to build and execute multi-agent systems using CrewAI. Through guided demonstrations, you will design specialized agents, define structured tasks, and create collaborative workflows. You will also explore how crews coordinate agent activities, how outputs are structured, and how multi-agent systems can automate complex processes such as research, planning, and content creation.
By the end of the program, you will be able to:
- Explain the core principles of AI agents, agentic AI, and multi-agent systems.
- Describe the CrewAI architecture, including agents, tasks, crews, and flows.
- Configure development environments and tools required to build CrewAI projects.
- Apply prompt engineering and context engineering techniques to guide agent reasoning.
- Design structured workflows and execution flows for multi-agent systems.
- Build and execute collaborative multi-agent crews to automate complex workflows.
This program is ideal for developers, AI practitioners, and technical professionals interested in building intelligent agent systems. Prior experience with Python programming and basic AI concepts will help learners gain the most value from the course.
Learners need a reliable internet connection, a modern web browser, and access to Python development tools. The course uses the CrewAI framework and LLM APIs, which do not require specialized hardware. Basic familiarity with Python and working with development environments is recommended.
Join this course to learn how to design, build, and deploy multi-agent AI systems that can automate workflows, coordinate tasks, and power intelligent AI-driven applications.
Learn the fundamentals of AI agents and agentic systems and how they differ from traditional prompt-based AI applications. Explore how agents operate, collaborate, and coordinate tasks within multi-agent environments. Examine the architecture of the CrewAI framework, including agents, tasks, crews, and flows, and understand how these components enable structured agent development. Build a strong technical foundation by preparing your development environment, installing CrewAI, and organizing projects for hands-on agent development.
Inclus
16 vidéos5 lectures4 devoirs
Afficher les informations sur le contenu du module
16 vidéos•Total 91 minutes
Specialization Introduction•6 minutes
Course Introduction•5 minutes
Marketing Team’s Struggle with Traditional AI•6 minutes
Introduction to Agentic AI•6 minutes
Core Concepts of Agentic AI•7 minutes
Difference between AI Agents and Agentic AI•6 minutes
Real-World Agentic AI Use Cases•5 minutes
Single-Agent vs Multi-Agent AI Architectures•7 minutes
How do Multi-Agent Systems Work?•6 minutes
What is CrewAI?•5 minutes
Understanding CrewAI Architecture•6 minutes
CrewAI vs Other AI Agent Frameworks•5 minutes
Preparing Your CrewAI Development Environment•4 minutes
Demonstration: Setting up Virtual Environment for Your Agentic System•5 minutes
Demonstration: Installing CrewAI with uv Package Manager•6 minutes
Demonstration: Understanding Project Structure and File Organization•6 minutes
5 lectures•Total 70 minutes
Course Syllabus•15 minutes
Types of Agents in AI•15 minutes
Business Case for Multi-Agent AI Systems•15 minutes
Best Practices for Structuring and Managing AI Agent Projects•15 minutes
Module Summary: Introduction to Multi-Agent AI Systems and CrewAI•10 minutes
4 devoirs•Total 33 minutes
Practice Assignment: Introduction to AI Agents and Agentic AI•6 minutes
Practice Assignment: Multi-Agent Systems and the CrewAI Framework•6 minutes
Practice Assignment: Development Environment Setup for CrewAI•6 minutes
Knowledge Check: Introduction to Multi-Agent AI Systems and CrewAI•15 minutes
Prompt, Context, and Flow Engineering for AI Agents
Module 2•3 heures à terminer
Détails du module
Discover how to design intelligent agents by applying prompt engineering, context engineering, and execution flow design. Learn how to configure large language models for different agent roles and evaluate trade-offs such as cost, latency, and performance. Explore techniques for crafting effective prompts that guide agent reasoning and behavior. Develop practical skills in structuring context and designing coordinated execution flows that allow multiple agents to collaborate effectively within an agent-based system.
Inclus
14 vidéos4 lectures4 devoirs
Afficher les informations sur le contenu du module
14 vidéos•Total 89 minutes
LLM Providers and Model Selection•8 minutes
Demonstration: Configuring Models per Agent Role•7 minutes
Demonstration: Evaluating Cost, Latency, and Accuracy Trade-offs•7 minutes
Principles of Effective Prompt Engineering for Agents•5 minutes
Core Prompting Techniques•7 minutes
Demonstration: Writing prompts to guide agent behavior and tone•7 minutes
Demonstration: Evaluating Prompt Impact Through Structured Comparison•5 minutes
Demonstration: Refining Prompts to Improve Agent Reasoning•7 minutes
Introduction to Context Engineering•7 minutes
Flow Engineering Fundamentals•5 minutes
Demonstration: Designing High-Quality Context for AI Agents•7 minutes
Demonstration: Context Quality in Action – Signal vs Noise•6 minutes
Demonstration: Flow Engineering for Multi-Agent Systems•6 minutes
Demonstration: Architecting Execution Flows in Multi-Agent Systems•4 minutes
4 lectures•Total 60 minutes
Model Selection Strategies for Agent-Based Applications•15 minutes
Prompt Engineering Best Practices for Agentic Systems•15 minutes
Context and Flow Design Patterns for Agent Systems•15 minutes
Module Summary: Prompt, Context, and Flow Engineering for AI Agents•15 minutes
4 devoirs•Total 33 minutes
Practice Assignment: Choosing and Configuring LLMs for Agents•6 minutes
Practice Assignment: Prompt Engineering for AI Agents•6 minutes
Practice Assignment: Context and Flow Engineering for Agent Systems•6 minutes
Knowledge Check: Prompt, Context, and Flow Engineering for AI Agents•15 minutes
Building and Executing Multi-Agent Crews
Module 3•3 heures à terminer
Détails du module
Learn how to build and execute collaborative agent systems using the CrewAI framework. Design AI agents with clearly defined roles and responsibilities, and create structured tasks that guide agent behavior and outputs. Gain hands-on experience assembling agents into collaborative crews, coordinating task execution, and managing multi-agent workflows. Develop practical skills to run and inspect agent systems, enabling you to build reliable multi-agent solutions that automate complex workflows.
Inclus
12 vidéos4 lectures4 devoirs
Afficher les informations sur le contenu du module
12 vidéos•Total 81 minutes
Key Elements for High-Performance Agents in CrewAI•7 minutes
Demonstration: Architecting Intelligence: Setting Up Your CrewAI Project•7 minutes
Demonstration: Designing High-Performance Agents with YAML Configuration•5 minutes
Understanding Tasks in CrewAI•5 minutes
Demonstration: Designing High-Precision Research and Strategy Tasks•7 minutes
Demonstration: Building a Self-Executing and Self-Evaluating Campaign Pipeline•7 minutes
Demonstration: Engineering Structured Intelligence: Schemas, Hooks, and Execution Lifecycle•7 minutes
Demonstration: Intelligent Model Assignment and Structured Multi-Agent Execution•7 minutes
Agent Collaboration Mechanisms•5 minutes
Demonstration: Execution Modes and Output Inspection in main.py•7 minutes
Demonstration: Single, Batch, and Async Execution Modes in main.py•7 minutes
Demonstration: Running Your CrewAI System from the Terminal•7 minutes
4 lectures•Total 60 minutes
Agent Design Patterns and Common Mistakes•15 minutes
Task Design and Output Structuring Best Practices•15 minutes
Collaboration and Orchestration Patterns for Multi-Agent Systems•15 minutes
Module Summary: Building and Executing Multi-Agent Crews•15 minutes
4 devoirs•Total 33 minutes
Practice Assignment: Designing AI Agents in CrewAI•6 minutes
Practice Assignment: Task Definition and Structured Outputs•6 minutes
Practice Assignment: Crew Assembly, Execution, and Collaboration•6 minutes
Knowledge Check: Building and Executing Multi-Agent Crews•15 minutes
Course Wrap-Up and Assessment
Module 4•2 heures à terminer
Détails du module
Consolidate your learning from the course and reflect on your progress in building AI agents with CrewAI. Apply your skills in a hands-on project by creating a multi-agent content creation system. Complete a final graded assessment to demonstrate your ability to design and execute collaborative agent workflows.
Inclus
1 vidéo1 lecture2 devoirs1 sujet de discussion
Afficher les informations sur le contenu du module
1 vidéo•Total 4 minutes
Course Summary•4 minutes
1 lecture•Total 30 minutes
Practice Project: Building a Multi-Agent Customer Support Assistant with CrewAI•30 minutes
2 devoirs•Total 60 minutes
End Course Knowledge Check: Building Your First AI Agent with CrewAI•30 minutes
Designing a Collaborative Multi-Agent Content Creation System Using CrewAI•30 minutes
1 sujet de discussion•Total 5 minutes
Describe Your Learning Journey•5 minutes
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This course is designed for developers, AI enthusiasts, and technical professionals interested in building intelligent multi-agent systems using CrewAI. Whether you are new to AI agents or have prior experience with AI tools, the course provides a clear introduction to agentic AI concepts and practical development workflows. Basic familiarity with Python programming will help you follow the hands-on demonstrations.
What will I learn in this course?
Throughout this course, you will learn how to design and build intelligent agents using the CrewAI framework. You will explore AI agent concepts, multi-agent architectures, prompt engineering, and context design to guide agent reasoning. The course also covers designing tasks, creating structured workflows, and assembling collaborative agent crews to automate complex processes.
What tools and technologies will be used in this course?
This course focuses on the CrewAI framework for building multi-agent systems. You will also work with Python, large language models (LLMs), prompt engineering techniques, and structured workflows. These tools help design agents, define tasks, and coordinate collaborative agent execution in real-world applications.
Do I need any prior experience with CrewAI or AI agents?
No prior experience with CrewAI or agent frameworks is required. The course begins with foundational concepts such as AI agents, agentic AI, and multi-agent systems before moving into practical development. Basic knowledge of Python and general programming concepts is recommended.
Will I get hands-on practice building AI agents?
Yes. This course includes demonstrations and practice assignments where you will design agents, define tasks, and assemble multi-agent crews using CrewAI. You will gain practical experience building agent workflows and executing them in a development environment.
How long will it take to complete the course?
The course is designed to be completed in about 4 weeks, with a recommended study pace of 3–4 hours per week. You can learn at your own pace and revisit lessons whenever needed.
Will I receive a certificate upon completion?
Yes. After successfully completing all modules, assignments, and the final project, you will receive a Certificate of Completion. This certificate validates your ability to design and build multi-agent systems using the CrewAI framework.
What makes this course different from other AI courses?
This course focuses specifically on multi-agent system development using CrewAI. Instead of only discussing AI concepts, it emphasizes hands-on learning through demonstrations, practical assignments, and real-world workflows. You will learn how to design agents, create collaborative crews, and automate complex tasks using structured agent architectures.
What career opportunities can this course lead to?
After completing this course, you will gain skills relevant to roles such as AI Developer, Machine Learning Engineer, AI Automation Engineer, and Intelligent Systems Developer. The ability to design multi-agent systems and automate workflows is becoming increasingly valuable across industries adopting AI-driven solutions.
Is this course suitable for someone with no prior experience in AI?
Yes. The course introduces agentic AI concepts from the ground up and gradually moves into practical development. Beginners with basic Python knowledge can follow the course and gain the skills needed to start building intelligent AI agent systems.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.