Description
The DeepLearning.AI Retrieval Augmented Generation (RAG) course offers an in-depth understanding of how to develop production-ready RAG applications. This course is designed for those with intermediate Python skills and a basic understanding of generative AI. Taught by Zain Hasan, an AI engineer and educator, the course covers the architecture, deployment, and evaluation of RAG systems.
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Participants will learn to design and implement every part of a RAG system, from retrievers and vector databases to large language models and evaluation platforms. The course emphasizes the importance of grounding model responses in relevant, often private or up-to-date data, which is crucial as LLMs are integrated into real products and workflows.
The course is structured into five modules, covering topics such as information retrieval, search foundations, vector databases, and text generation. Students will engage in hands-on programming assignments, building components of a RAG system using real-world datasets from domains like e-commerce, media, and healthcare.
Throughout the course, learners will explore critical tradeoffs, such as when to use hybrid retrieval, how to manage context window limits, and how to balance latency and cost. By the end of the course, participants will have the skills to build, evaluate, and evolve RAG systems, moving beyond proof-of-concept demos into real-world deployment.
The course is available on Coursera and offers a certificate upon completion. It is self-paced, allowing learners to progress at their own speed, with an estimated commitment of 5 hours per week over a month. Financial aid is available for those who qualify.
- CategoryCorporate Training & E-Learning
- Pricing ModelPaid with financial aid
- PlatformsCoursera
DeepLearning.AI Retrieval Augmented Generation Course's Core Features
Intermediate Python skills required
Certificate upon completion
Self-paced learning
5 modules covering RAG systems
Hands-on programming assignments
Real-world datasets
Focus on grounding model responses
Taught by Zain Hasan
How to use DeepLearning.AI Retrieval Augmented Generation Course?
Enroll: Sign up for the course on Coursera
Learn: Complete modules and assignments
Apply: Build RAG systems with real datasets
Certify: Earn a certificate upon completion
DeepLearning.AI Retrieval Augmented Generation Course's Use Cases
- Healthcare applications
- E-commerce solutions
- Media content management
- Customer support
- Domain-specific chatbots
