LangGraph- Develop LLM powered AI agents with LangGraph (Udemy.com)

Hi Eden, This Ahmed Fayad, First of all I want to say that your course is great and really love it but here is some notes Want to add general framework to build lang-graph application and more training at libraries like typing and pydantic the course is great and valuable but if increase the uinfied framework to build any langgraph app and start inject special cases so start from general than go deep to specific but still wonderful course Best Wishes, Ahmed Fayad

There is big redundancy between the other course you have created and this one. The content itself is still good, but there should be a clear distinction between the 2 courses what to skip or what to ignore if you have done the other course.

I loved the way the trainer is explaining the concepts and also the practical implementation of each and every langgraph he has covered. After his explanation the implementation becomes so easy.

This course has enabled me to grasp complex langgraph concepts through building hands on applications. Using the examples I am able to build curated applications for my use cases.

This is an awesome course to begin with. Being from eng background, I always used to wonder why DS folks do all of this thing. What goodness ir brings, this course helped me in clarifying that doubt.

Very good, this course is very explainable. Get very detailed software engineering and API related insight on agentic developing. Thanks for Elan's hardworking on making these course.

This is a strong, hands-on course for experienced software engineers who want to move beyond basic LLM usage and build real, production-style agentic systems with LangGraph. What I appreciated most is the practical, end-to-end approach. The course does not stop at simple examples, but walks through how to design, structure, and reason about more advanced agent workflows, including multi-agent setups, reflection patterns, and different RAG strategies. The coverage of the LangGraph ecosystem, including Studio and Cloud concepts, is also very useful for understanding where these tools are heading. The explanations assume solid engineering fundamentals, which I see as a positive. This is not a beginner course, and it respects the learner’s time by focusing on real implementation details rather than high-level theory. I also found value in seeing how LangGraph fits within the broader LangChain ecosystem, and how to reason about agent design choices instead of blindly following patterns. Overall, a very good course for backend, fullstack, or AI engineers who already have experience with Python and LangChain and want to build more robust, maintainable LLM agent systems.

Thanks for the course! I got a good understanding of langgraph. My suggestions: the last two parts are too theoretical; I'd like to implement a simple chat with Human in the Loop.

Awesome course. A lot of good information. Really takes you through and clearly explains langraph and give you examples to follow as well.

It helped me quickly grasp the overall components of Langraph, but it didn't provide the level of understanding required by the company. Given the short lecture time, it was fortunate; had the lectures been longer, I would have given an even worse rating.