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

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.

SB
One of the great course to understand the importance of controllable outputs from LLMs
KM
Incredible insight to LLMs and understanding the continuous issues with them. Should be mandatory for any person working with Data, computers and optimzation
JM
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
Excellent videos and resources, especially the code examples. 10/10 course
RR
Another amazing class! I will go through this one again.
TB
The exams suggest using ChatGPT or Gemini, which makes them too easy.
RF
One of the most enjoyable courses I have found on Coursera. Excellent lectures and content.
JR
Need more in terms of graded knowledge assessments/assignments.
显示:20/35
Not what I expected. While the course material is well presented and the code examples quite good, the name of the course is AI architecture in Python. I was expecting programming assignments and tests without which the retention is considerably reduced.
One of the most enjoyable courses I have found on Coursera. Excellent lectures and content.
The exams suggest using ChatGPT or Gemini, which makes them too easy.
Need more in terms of graded knowledge assessments/assignments.
it`s a good couse for beginners.
The course covers an important subject in developing AI Agents. But, we don't get any good references that can help to complete the learning and get some other approaches on the subject. Also, I missed some good practices.
Un curso robusto, donde se aprende de buenas tecnicas para programar agentes, es importante leer y comprender las lecturas sugeridas, hay muchos codigos e ideas super utilies que se implementan en estas como el diseño de agentes auxiliares como definir los squema json y como realizar el buen diseño del pront para el agente.
Great Course for people who want to get started with Agentic AI. Can't wait to explore other courses. Also you should only take this course if you are familiar with Python. Without python you wont be able to understand Module 4 and Module 5. It gets a bit more Python driven in the last two modules
Most insteresting course so far at least for me - looking forward to more courses like this. Multi-agents has been my favorite topic for a long time... I liked code samples which illustrate concepts and make them more practical
One of the great course to understand the importance of controllable outputs from LLMs
Excellent videos and resources, especially the code examples. 10/10 course
Super useful , mind opening, REALLY useful also for managers and PM
Amazing course, thanks for your insights and techings Jules
Another amazing class! I will go through this one again.
Love it! Simple to understand, well presented
Very practical and easy to follow, thank you.
Very informative and great content
Great course content
good explanations
Great information