Large Language Models and Embeddings for Retrieval Augmented Generation

Issued by Constellate from ITHAKA

The earner of this badge has gained hands-on experience working with innovative models and techniques, empowering them for use research with a focus on retrieval augmented generation (RAG) solutions - RAG is a groundbreaking approach that combines the strengths of pre-trained language models with external knowledge retrieval, enabling the generation of highly informative and contextually relevant text.

Type Learning
Level Foundational
Time Days
Cost Free

Additional Details

Skills

Data Analysis
Large Language Models (LLMs)
Machine Learning (ML)
Performance Optimization
Retrieval Augmented Generation
Text Analysis
Vector Embeddings

Earning Criteria

Complete 1-week, 3-day course in Large Language Models and Embeddings for Retrieval Augmented Generation, consisting of 4.5 hours of e-learning.