• Duration

    30 Minutes

  • Level

    Intermediate

  • Course Type

    Short Course

What you'll Learn

  • Understand the concepts of Retrieval-Augmented Generation (RAG).

  • Learn to work with LangChain.

  • Build interactive and visually appealing apps using Streamlit.

  • Gain hands-on experience with practical RAG use cases.

About the Instructor

Dipanjan Sarkar - Head of Community and Principal AI Scientist, Analytics Vidhya

Dipanjan Sarkar is a distinguished Lead Data Scientist, Published Author, and Consultant, having a decade of extensive expertise in Machine Learning, Deep Learning, Generative AI, Computer Vision, and Natural Language Processing. His leadership spans Fortune 100 enterprises to startups, crafting end-to-end data products and pioneering Generative AI upskilling programs. A seasoned mentor, Dipanjan advises a diverse clientele, from novices to C-suite executives and PhDs, across Advanced Analytics, Product Development, and Artificial Intelligence.
About the Instructor

Who Should Enroll?

  • Learn to combine tools like LangChain and Streamlit to build dynamic applications.

  • Upskill by creating impactful RAG-based systems to handle complex queries and data workflows.

  • Build intuitive applications that integrate retrieval and generation for enhanced user experience.

FAQ

  • What is LangChain?

    LangChain is a framework for building applications powered by language models, offering seamless integration with data sources and retrieval techniques.

  • What is Streamlit?

    Streamlit is a Python library that simplifies creating interactive web applications, making it ideal for visualizing and presenting your RAG applications.

  • Will I receive a certificate upon completion?

    Yes, you will receive a certificate of completion after successfully finishing the course and assessments.

  • Who is this course for?

    This course is designed for developers, data scientists, and AI enthusiasts who want to create advanced AI applications. Basic knowledge of Python and familiarity with LLMs is recommended.

  • Does the course include hands-on projects?

    Yes, the course includes practical, hands-on projects where you’ll build end-to-end App based on RAG Application with LangChain and Streamlit.