7 days ago
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In this hands-on course, instructor Megan Silvey shows you how to utilize Streamlit to build web applications. This open-source Python framework has become a key tool for data scientists and AI/ML engineers. In particular, learn how to design and deploy a retrieval‑augmented generation (RAG) document Q&A chatbot in Streamlit using Python and OpenAI’s API. Get started with an overview of Streamlit and large language models (LLMs), along with best practices for working with AI and APIs. Next, find out how to prepare text data to create a RAG pipeline that integrates into a Streamlit chat interface. By the end of this course, you’ll be prepared to test, maintain, and deploy a fully functional chatbot on Streamlit Community Cloud.
This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out the “Using GitHub Codespaces with this course” video to learn how to get started.\
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