Building a RAG Solution from Scratch
Released 01/2025
With Axel Sirota
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 53m 54s | Size: 338 MB
Learn to design, implement, and optimize RAG systems for chatbots and decision support, while exploring current research and ethical considerations.
Course details
In this course, Axel Sirota introduces Retrieval-Augmented Generation (RAG) as a powerful technique for enhancing the capabilities of Large Language Models (LLMs). Learn the foundational concepts and practical applications of RAG, focusing on creating chatbots and decision support systems across various domains. Using the MIMIC-III dataset to create a healthcare chatbot that can answer questions or suggest a diagnosis as an example, get hands-on experience in building RAG systems with TensorFlow, Keras, and HuggingFace. By the end of the course, you will be equipped to deploy RAG solutions that integrate robust retrieval mechanisms with generative models, applicable in fields like healthcare, legal, and customer service.
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