Coursera
MOOC / Non-credit
0
Introduction to Retrieval Augmented Generation (RAG)
About this course
In this 2-hour project-based course, you will learn how to import data into Pandas, create embeddings with SentenceTransformers, and build a retrieval augmented generation (RAG) system with your data, Qdrant, and an LLM like Llamafile or OpenAI. This hands-on course will teach you to build an end-to-end RAG system with your own data using open source tools for a powerful generative AI application.
B
75/100
CourseAsk score
- What the provider tells you
- 24/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
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What you'll learn
- import data using Pandas
- create embeddings with SentenceTransformers
- build a RAG system using Qdrant
- apply a language model like Llamafile or OpenAI for generative tasks
Machine Learning
Artificial Intelligence
#pandas
#machine learning
#generative ai
#data processing
#data analysis
#rag
#embeddings
#openai
#llm
#qdrant
#sentence transformers
$9.99
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