Mastering Generative AI Project: RAG and LangChain App
Get valuable practical experience building a real-world gen AI application that you can add to your portfolio and showcase your skills in job interviews.
Get valuable practical experience building a real-world gen AI application that you can add to your portfolio and showcase your skills in job interviews.
This hands-on project course gives you the opportunity to build a real-world generative AI application that demonstrates your expertise to potential employers. You'll work with LangChain document loaders to upload documents from various sources and implement text-splitting strategies to enhance model responsiveness. The course teaches you to use Watsonx for document embedding and leverage vector databases to store these embeddings. You'll create a retriever using LangChain to fetch relevant documents based on queries, implement retrieval-augmented generation (RAG), build a functional QA bot, and design a Gradio interface for user interaction. By completing this project, you'll have tangible evidence of your generative AI engineering capabilities to showcase in interviews.
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What you'll learn
Gain practical experience building a real-world generative AI application for your portfolio Learn to load and process documents using LangChain and implement effective text-splitting strategies Create and manage vector databases for storing document embeddings Develop retrievers that efficiently fetch relevant documents based on user queries Implement retrieval-augmented generation (RAG) to improve model responses Build a functional QA bot using LangChain and large language models Design an interactive Gradio interface for users to engage with your AI application Apply your generative AI engineering skills to a tangible project you can discuss in interviews
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 3 modules in this course
This practical project course enables students to apply generative AI engineering skills in a real-world context. Participants will build a complete AI application that showcases their expertise in retrieval-augmented generation (RAG) and LangChain. The course provides hands-on experience with document loading and processing, implementing text-splitting strategies to optimize model performance, and creating vector databases for efficient document retrieval. Students will learn to generate document embeddings using Watsonx.ai and implement retrievers that can effectively fetch relevant information based on user queries. The project culminates in the development of an interactive question-answering bot with a user-friendly Gradio interface. This capstone-style project offers valuable portfolio material that demonstrates practical AI engineering skills to potential employers and reinforces theoretical knowledge through application.
Document Loader Using LangChain
Module 1
RAG Using LangChain
Module 2
Create a QA Bot to Read Your Document
Module 3
Fee Structure
Payment options
Financial Aid
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Frequently asked questions
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