๐Ÿ”ฌ

Data Scientist - LLM Applications & RAG Systems

LLM Applications & RAG Systems for Data Scientist: A comprehensive guide to mastering LLM Applications & RAG Systems as a Data Scientist. Learn recommended tools, practical applications, and resources to develop this critical AI skill.

AI/ML Foundations & LLMs

Modern AI/ML foundations including LLM applications, advanced frameworks, and model optimization techniques.

Advanced AI Techniques

Cutting-edge AI techniques including multimodal AI, reinforcement learning, and federated learning systems.

AI Infrastructure & MLOps

Building scalable AI infrastructure, MLOps pipelines, and production-ready AI systems with monitoring.

AI-Driven Data Engineering

AI-enhanced data engineering including vector databases, real-time pipelines, and intelligent data quality systems.

AI Research & Innovation

Research implementation, AI safety, and contributing to the advancement of AI technology and ethics.

LLM Applications & RAG Systems

Skill Description

Building RAG systems, fine-tuning LLMs, implementing AI agents, and creating robust prompt engineering frameworks for enterprise applications.

Recommended Tools
Essential AI tools and platforms for this skill
Practical Examples
Real-world applications and use cases
  • Build RAG systems for enterprise knowledge bases
  • Fine-tune LLMs for domain-specific applications
  • Implement AI agents and multi-step reasoning workflows
  • Create prompt engineering frameworks for consistent outputs