Advanced RAG
Pragmatic AI Labs
Master cutting-edge RAG techniques to enhance LLM applications. Learn embedding strategies, document processing, and advanced retrieval methods for building high-performance AI solutions in enterprise environments. 10 hands-on labs and exercise to "learn by doing".
About this Course
Transform your ability to build enterprise-grade AI applications using advanced Retrieval-Augmented Generation (RAG) techniques. This comprehensive course is designed for AI engineers, MLOps professionals, and software developers seeking to master LLM implementation. Key Course Features: Hands-on labs and practical exercises with real-world applications Deep dive into embedding vectors and document processing strategies Advanced retrieval techniques including hybrid search and multimodal retrieval Interactive weekly Q&A sessions with industry experts Lifetime access to course materials and video recordings Perfect for: AI and MLOps engineers Solutions architects Enterprise architects Software developers working with AI Technical professionals transitioning to AI development Prerequisites: Basic understanding of AI/ML concepts Programming experience Familiarity with Python
What You'll Learn
- Implement enterprise-grade RAG systems from scratch
- Master vector databases and embedding techniques
- Design effective document chunking strategies
- Create semantic search implementations
- Build hybrid search and reranking systems
- Develop multimodal retrieval solutions
- Optimize query-document alignment techniques
- Deploy contextual retrieval systems
- Implement advanced document enrichment strategies
- Create production-ready LLM applications
Instructors
Guy Ernest
Chief Engineering Officer