Description
AI Agents with Python and CrewAI. This course explores how to build autonomous intelligent agents using Python and the CrewAI framework to automate processes, search the web, communicate with databases, and send messages. Large Language Models (LLMs) can answer questions, but they don’t have the ability to take independent actions. They can’t search the web for up-to-date information, query a database, send an email, or trigger a notification message. This course fills that gap by teaching you how to build autonomous AI agent systems—systems that can perform practical tasks in addition to analyzing and thinking. The course starts with the basics, showing what stations have shaped modern AI, how we got from simple language models to agent-based AI, and the differences between an AI agent and a simple chatbot. Key concepts such as roles, goals, tools, tasks, and groups are explored to demonstrate why multi-agent coordination is one of the most powerful design patterns in applied AI today. The main part of the course focuses on the CrewAI framework, a Python framework for building collaborative multi-agent systems. Participants will experience going from scratch to building fully functional pipelines through three practical scenarios. In the first scenario, the problem of knowledge constraints on models is investigated and solved by giving them web search access via the SerperDevTool; a custom email sending tool is also built with the Brevo API to design a two-agent system where one agent does the research and the other emails the results. In the second scenario, custom SQLite query and Excel report generation tools are created to allow two specialized agents to collaborate to check inventory and send reports; this section also teaches how to work with alternative models such as DeepSeek. In the third scenario, a three-agent system is designed that extracts web data with Selenium, sends email summaries, and sends confirmation SMS. By the end of the course, learners will fully understand how to define agents, build custom tools, coordinate multi-agent workflows, and connect external services through Jupyter Notebooks.
What you will learn
- Building Multi-Agent Systems: Design multi-agent AI systems with CrewAI that autonomously research, report, and inform with Python.
- Custom tool development: Building specialized tools to connect AI agents to real-world APIs, databases, email services, and web mining tools.
- Workflow orchestration: The coordination of sequential pipelines in which expert agents collaborate to perform complex tasks.
- External service integration: Connect external services such as web search, SQLite, Excel, Selenium, email, and SMS to agent pipelines.
- Solving the knowledge constraint problem: Using web search tools like SerperDevTool to give agents access to up-to-date information.
- Working with diverse language models: Using different models such as DeepSeek alongside other language models to optimize system performance.
This course is suitable for people who:
- Intermediate Python Developers: Programmers who want to advance their skills towards developing intelligent systems.
- AI enthusiasts: People who want to go beyond chatbots and build autonomous agents.
- Automation Engineers: Professionals who seek to automate complex organizational processes with artificial intelligence.
- Software developers: People who want to connect various services like APIs, databases, and Selenium to language models.
AI Agents with Python and CrewAI course details
- Publisher: Udemy
- Lecturer: Dr. Alexander Schlee
- Training level: Beginner to advanced
- Training duration: 2 hours and 57 minutes
- Number of lessons: 12
Course syllabus in 2026/5
Prerequisites for the AI Agents with Python and CrewAI course
- Basic Python Knowledge
Course images
Sample course video
Installation Guide
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Subtitles: None
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
2.3 GB