In this course, you will explore advanced AI engineering concepts, focusing on the creation, use, and management of embeddings in vector databases, as well as their role in Retrieval-Augmented Generation (RAG).

Retrieval-Augmented Generation (RAG) with Embeddings & Vector Databases
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Retrieval-Augmented Generation (RAG) with Embeddings & Vector Databases
This course is part of AI Engineering Specialization

Instructor: Guil Hernandez
7,314 already enrolled
Included with
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Understand and Create Embedding
Utilize Vector Databases
Retrieval-Augmented Generation (RAG)
Skills you'll gain
- Category: LLM Application
- Category: Databases
- Category: Embeddings
- Category: Virtual Environment
- Category: Development Environment
- Category: Artificial Intelligence
- Category: Retrieval-Augmented Generation
- Category: System Configuration
- Category: Large Language Modeling
- Category: AI Integrations
Tools you'll learn
- Category: Vector Databases
- Category: OpenAI API
- Category: Generative AI
- Category: OpenAI
Details to know

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Assessments
3 assignments
Taught in English
Build your subject-matter expertise
This course is part of the AI Engineering Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate

There are 3 modules in this course
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Instructor

Guil Hernandez
Scrimba
7 Courses38,585 learners
Offered by

Scrimba
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