Project: Generative AI Applications with RAG and LangChain

About this course

Get ready to put your generative AI engineering skills into practice! In this hands-on guided project, you’ll apply the knowledge and techniques gained throughout the previous courses in the program to build your own real-world generative AI application. You’ll begin by filling in key knowledge gaps, such as using LangChain’s document loaders to ingest documents from various sources. You’ll then explore and apply text-splitting strategies to improve model responsiveness and use IBM watsonx to embed documents. These embeddings will be stored in a vector database, which you’ll connect to LangChain to develop an effective document retriever. As your project progresses, you’ll implement retrieval-augmented generation (RAG) to enhance retrieval accuracy, construct a question-answering bot, and build a simple Gradio interface for interactive model responses. By the end of the course, you’ll have a complete, portfolio-ready AI application that showcases your skills and serves as compelling evidence of your ability to engineer real-world generative AI solutions. If you're ready to elevate your career with hands-on experience, enroll today and take the next step toward becoming a confident AI engineer.

Course objectives

• build a real-world generative AI application
• enhance retrieval accuracy using retrieval-augmented generation (RAG)
• create a complete, portfolio-ready project