This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization. Unlock the potential of LangChain and large language models (LLMs) to create innovative applications. You will develop 15 real-world applications using Python, integrating tools like OpenAI, Hugging Face, and LLAMA 2. The specialization is structured around practical projects that introduce key concepts in sequential modules. Topics include memory management, text embeddings, prompt engineering, and chain models. With each project, you’ll master unique features of LangChain, such as building question-answering systems and conversational agents, while performing data processing tasks. Unlock the potential of LangChain and LLMs with this comprehensive specialization designed for AI enthusiasts and developers. From setting up your development environment to mastering core principles of LLMs. Designed for AI enthusiasts and developers with basic Python knowledge, this specialization takes you from setting up your development environment to mastering core principles of LLMs. By the end, you will be able to build intelligent applications, understand memory management, prompt engineering, and agent architecture, and create adaptive AI agents for real-world challenges.
LL
Codes are outdated. But still offers a practical introduction to the world of LLMs and Langchain.
NL
Good introduction course. Really good if you already know LLMs and want to scale up.
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These may not be all the possibilities of Apps that can be developed using Langchain and LLM, but this course certainly shows the way. Each of the App shows up innovative ways to use Langchain and teaches the steps in detail with code sample. The explanation is also very crisp and clear. I enjoyed thoroughly going through this training. Highly recommended course.
The course is very useful for learning Langchain and other tools like AI web services having many examples and applications. Most of the applications are up to date with the current Langchain version or can be easily modified to work. Sometimes one needs to use the old version of libraries in the requests.txt file.
the langchain and other used frameworks are deprecated. so will have to find the new alternatives yourselves. other than that the teaching method and course content was good
This course is good at explaining concepts of using Langchain and Langgraph, however if you are learning Langchain and Langgraph in 2025 and onwards, this course is outdated in multiple ways. Right off the bat, the instructor starts using the langchain library with OpenAI as the model, however the commands/libraries he is using have been deprecated. He says to download langchain using pip, and in the code he imports OpenAI through the langchain library, but that way of importing models has been deprecated, at least for OpenAI. You have to instead download langchain-openai which is it's own library and instead import ChatOpenAI instead of the standard OpenAI that the instructor says to do. A lot of the hugging face libraries he mentions are also deprecated. I am currently struggling to keep up because he continues to use outdated models, which makes it extremely difficult to practice and learn. When he gets into Spaces in Hugging Face, he is using the Streamlit as the Space SDK, however Streamlit is no longer supported as a SDK in Spaces, the only options are Gradio, Docker, and Static. I essentially have to skip a huge chunk of the course because of this minor deprecation. I would've hoped for the course to be continuously updated with the latest libraries so the students can keep up and actually do what the instructor is saying.
they have a space named dialogue, and ask questions about information you don't have learn yet...i'm here looking how to unenroll for packh
I had to stop the course because it is not really reflecting the current layout of LangChain
Extremely poor quality content. Not worthy of being on Coursera.
Outdated course content, some codes are not working!
langchain codes are outdated. No more runs.