This course introduces the powerful concept of Retrieval-Augmented Generation (RAG), a technique used to optimize the performance, accuracy, and cost of generative AI systems. Focused on building AI pipelines with LlamaIndex, Deep Lake, and Pinecone, this course will equip you with the skills to create robust AI models capable of handling complex datasets and delivering traceable, context-aware outputs.
RAG-Driven Generative AI
Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Scale RAG pipelines to handle large datasets efficiently
Implement techniques that reduce hallucinations and improve response accuracy
Customize and scale RAG-driven AI systems across different domains
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
March 2026
Assessments
10 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
There are 10 modules in this course
In this section, we explore Retrieval Augmented Generation (RAG) frameworks, focusing on naive, advanced, and modular configurations. We implement Python-based RAG systems for improved AI accuracy and adaptability.
What's included
2 videos6 readings1 assignment
In this section, we cover building and managing RAG pipelines with Deep Lake and OpenAI for efficient AI data handling.
What's included
1 video4 readings1 assignment
In this section, we explore index-based RAG pipelines using LlamaIndex, Deep Lake, and OpenAI to enhance traceability, precision, and control in AI-driven data retrieval and generation.
What's included
1 video5 readings1 assignment
In this section, we explore multimodal modular RAG for drone technology, integrating text and image data retrieval, generation, and performance evaluation using LLMs and MMLLMs.
What's included
1 video5 readings1 assignment
In this section, we explore adaptive RAG with human feedback loops, focusing on improving retrieval quality and integrating expert input.
What's included
1 video4 readings1 assignment
In this section, we explore scalable RAG techniques for bank customer data using Pinecone and OpenAI. Key concepts include EDA, vector scaling, and AI-driven recommendations to reduce churn.
What's included
1 video7 readings1 assignment
In this section, we explore building scalable RAG systems using knowledge graphs, implementing the Wikipedia API, populating a Deep Lake vector store, and constructing a LlamaIndex knowledge graph for semantic search.
What's included
1 video5 readings1 assignment
In this section, we explore dynamic RAG using Chroma and Llama, focusing on embedding and querying temporary data for real-time decision-making with open-source tools.
What's included
1 video5 readings1 assignment
In this section, we explore RAG data reduction through fine-tuning, focusing on preparing JSONL datasets and evaluating model performance with OpenAI metrics for improved accuracy and cost-effectiveness.
What's included
1 video3 readings1 assignment
In this section, we explore RAG pipeline implementation for video generation, embedding video comments in Pinecone, and enhancing labels with GPT-4o analysis for efficient video stock production.
What's included
1 video7 readings1 assignment
Instructor
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
More questions
Financial aid available,