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There are 2 modules in this course
Ready to boost your AI career by mastering next-level retrieval techniques for intelligent search and summarization? This hands-on course takes you deep into the world of Retrieval-Augmented Generation (RAG), advanced retrievers, and vector databases such as FAISS and Chroma DB. You'll gain the cutting-edge skills businesses need to design and build scalable, high-performance RAG applications that drive smarter search and response capabilities.
During the course, you'll learn how to differentiate retrieval patterns, implement similarity search using FAISS, and integrate LangChain with modern UI frameworks such as Gradio. Then, in practical labs and guided projects, you'll get hands-on experience building an end-to-end AI application that retrieves, summarizes, and answers questions in real time.
From multi-query and parent document retrievers to semantic vector search and evaluation, this course will give you the skills to improve internal search engines, chatbot accuracy, and content recommendation systems.
Enroll today and enhance your portfolio with hands-on experience building AI that understands context—and delivers results.
In this module, you will get a deep dive into advanced retrievers and retrieval patterns, equipping you with the skills to implement and optimize advanced retrieval strategies within a RAG system. Participants will explore various retriever types through video lectures and hands-on labs, including vector store-backed, multi-query, self-querying, and parent document retrievers. Learners will apply these techniques using LangChain and LlamaIndex, gaining practical experience in building smarter search capabilities and enhancing retrieval efficiency in AI-driven applications.
Reading: Helpful Tips for Course Completion•5 minutes
Reading: Cheat Sheet: Advanced Retrievers for RAG•15 minutes
Build a Comprehensive RAG Application
Module 2•4 hours to complete
Module details
In this module, you will explore FAISS, a powerful vector database used for efficient similarity search. You will compare FAISS with Chroma DB to understand its unique advantages and applications. Through hands-on experience, you will build a semantic search engine using FAISS in a non-RAG setting, demonstrating its versatility beyond retrieval-augmented generation (RAG). Finally, you will develop a fully functional RAG application, integrating FAISS, an advanced retriever, and a front-end UI built with Gradio. This module reinforces key RAG concepts while guiding learners through the process of creating an end-to-end AI-powered application.
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MK
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Reviewed on Mar 13, 2026
Its a wonderful course I got so far. I completed this and got good grasp in advanced vector DBs and finally ended with good profile of Gen AI Engineer lead role. Must watch.
What career opportunities open up for me if I take this course?
By mastering advanced RAG techniques and vector databases such as FAISS and Chroma DB, and learning to integrate with LangChain and Gradio, you'll be well-prepared for roles such as AI Developer, Data Engineer, AI Application Architect, Search Algorithm Engineer, or Technical Product Manager. These roles involve developing intelligent, efficient search systems, optimizing retrieval methods, and designing AI-driven applications that utilize advanced retrieval techniques.
Do I need a background in machine learning to take this course?
No, machine learning experience is not a requirement! Although Python programming and an understanding of APIs and web development are recommended, this course focuses on implementing and optimizing retrieval systems using tools such as FAISS, LangChain, and Gradio. It's designed for developers and engineers looking to enhance their skills in building advanced search-driven AI applications without delving deeply into machine learning model training.
How does this course differ from traditional search or database management training?
Traditional courses often focus on basic query optimization or relational databases. In contrast, this course dives deep into Retrieval-Augmented Generation (RAG) and advanced vector-based retrieval systems. You'll explore cutting-edge techniques such as similarity search, vector databases, and AI-driven retrieval strategies, applying these concepts to create dynamic, real-time, and context-aware search experiences. It's perfect for developers looking to leverage modern technologies for AI-enhanced search systems.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.