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Vanderbilt University

AI Agents and Agentic AI Architecture in Python

Master the Art of Building Intelligent Python Agents That Think, Reason, and Act Unlock the full potential of Python for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Python & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Python's robust ecosystem and industry-standard capabilities. This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Python & Generative AI course to explore advanced patterns for building truly intelligent agents in Python. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Python's powerful frameworks and libraries. What You'll Learn: - Self-Prompting Patterns in Python: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Python implementations - Python-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture - Document-as-Implementation: Use Python's powerful file handling to create systems where human-readable documents become executable business logic - Multi-Agent Collaboration with Python: Design sophisticated memory sharing and coordination mechanisms between specialized Python agents - Progress Tracking & Planning: Implement robust planning and reflection capabilities using Python's comprehensive tooling - Python Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Python's exception handling and security features By the end of this course, you'll be equipped to build complex, production-ready agent systems in Python that can reason across multiple domains, handle complex workflows, and safely interact with real-world systems. Whether you're building productivity tools, automating complex business processes, or creating intelligent assistants, you'll have the Python-specific knowledge to implement agentic AI solutions that provide genuine business value. This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.

状态:Business Logic
状态:Coordination
初级课程小时

精选评论

SB

5.0评论日期:May 11, 2025

One of the great course to understand the importance of controllable outputs from LLMs

KM

4.0评论日期:Sep 1, 2025

Incredible insight to LLMs and understanding the continuous issues with them. Should be mandatory for any person working with Data, computers and optimzation

JM

4.0评论日期:Sep 22, 2025

Content and explanations are great, I think a series of exercises and quizzes would really help making sure one can take the most out of it.

JF

5.0评论日期:Aug 2, 2025

Excellent videos and resources, especially the code examples. 10/10 course

RR

5.0评论日期:Aug 23, 2025

Another amazing class! I will go through this one again.

TB

4.0评论日期:Aug 18, 2025

The exams suggest using ChatGPT or Gemini, which makes them too easy.

RF

5.0评论日期:Jun 20, 2025

One of the most enjoyable courses I have found on Coursera. Excellent lectures and content.

JR

4.0评论日期:Oct 25, 2025

Need more in terms of graded knowledge assessments/assignments.

所有审阅

显示:20/35

Rony Atoun
3.0
评论日期:Apr 23, 2025
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5.0
评论日期:Jun 21, 2025
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4.0
评论日期:Aug 19, 2025
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评论日期:Oct 26, 2025
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4.0
评论日期:Aug 24, 2025
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3.0
评论日期:May 25, 2025
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5.0
评论日期:Dec 10, 2025
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评论日期:Aug 19, 2025
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5.0
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5.0
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Raini
5.0
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5.0
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5.0
评论日期:Aug 1, 2025
KELLEN COLEMAN
5.0
评论日期:Jun 30, 2025