PHAROS AI Factory announces the 9th Course of its Training Series, Topic AI4LanguageCulture: “RAG End-to-End: Architecture, Retrieval, Generation and Evaluation“, held online via Zoom on July 7th, 2026.
Presentation language: Greek
Audience: Machine Learning Engineers, AI Engineers, Data Scientists, Academic Researchers, Language and Culture Experts
Location: Online via Zoom (you will get the zoom link upon registration)
Learning Objectives:
- Explain the core principles and architecture of Retrieval-Augmented Generation systems.
- Understand why RAG improves factuality, grounding, transparency and access to external knowledge.
- Describe the main RAG pipeline stages, from ingestion and preprocessing to retrieval and response generation.
- Identify design choices for chunking, embeddings, vector storage, retrieval, prompting and answer grounding.
- Evaluate retrieval quality, generation quality and end-to-end RAG behaviour.
Learning Outcomes:
After completing the course, participants will have:
- A clear understanding of the main components and design paradigms of RAG systems.
- Practical familiarity with document preparation, chunking, embedding generation, vector indexing and similarity-based retrieval.
- Hands-on experience in constructing a working RAG pipeline using Python and contemporary tools.
- The ability to connect retrieved evidence with LLM-based answer generation in a grounded and transparent manner.
- Familiarity with evaluation approaches for retrieval, generation, faithfulness, groundedness and overall RAG performance.
- An understanding of how RAG can support Greek-language applications, including public-service information retrieval and conversational assistance.
- The skills to analyse, evaluate and improve RAG systems for real-world deployment
The course’s agenda can be found here.
Register to attend by filling out the form here.
