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SUMMARY:PHAROS Training Series - Course 9 "RAG End-to-End: Architecture\, 
 Retrieval\, Generation and Evaluation"
DTSTART;VALUE=DATE-TIME:20260707T080000Z
DTEND;VALUE=DATE-TIME:20260707T121500Z
DTSTAMP;VALUE=DATE-TIME:20260703T055901Z
UID:indico-event-213@events.grnet.gr
DESCRIPTION:\n\nPHAROS AI Factory announces the 9th Course of its Training
  Series\, under the title "RAG End-to-End: Architecture\, Retrieval\, Gene
 ration and Evaluation"\, under the topic AI4LanguageCulture\, held online
  via Zoom.  \n\nDate: July 7th\, 2026\, at 11:00 EEST \n\nLocation: On
 line via Zoom\n\nPresentation Language: Greek\n\nAudience:  Machine Learn
 ing Engineers\, AI Engineers\, Data Scientists\, Academic Researchers\, La
 nguage and Culture Experts  \n\nPrerequisites: Basic Python knowledge \n
 \nLearning Objectives: \n\n• Explain the core principles and architectu
 re of Retrieval-Augmented Generation systems.\n • Understand why RAG im
 proves factuality\, grounding\, transparency and access to external knowle
 dge.\n • Describe the main RAG pipeline stages\, from ingestion and pre
 processing to retrieval and response generation.\n • Identify design ch
 oices for chunking\, embeddings\, vector storage\, retrieval\, prompting a
 nd answer grounding.\n • Evaluate retrieval quality\, generation qualit
 y and end-to-end RAG behaviour.\n\nLearning Outcomes: \n\n\nAfter complet
 ing the course\, participants will have: \n\n\n\n\n	\n	A clear understand
 ing of the main components and design paradigms of RAG systems. \n	\n\n\n
 \n\n\n	\n	Practical familiarity with document preparation\, chunking\, emb
 edding generation\, vector indexing and similarity-based retrieval. \n	
 \n\n\n\n\n\n	\n	Hands-on experience in constructing a working RAG pipeline
  using Python and contemporary tools. \n	\n\n\n\n\n\n	\n	The ability to c
 onnect retrieved evidence with LLM-based answer generation in a grounded a
 nd transparent manner. \n	\n\n\n\n\n\n	\n	Familiarity with evaluation app
 roaches for retrieval\, generation\, faithfulness\, groundedness and ove
 rall RAG performance. \n	\n\n\n\n\n\n	\n	An understanding of how RAG can 
 support Greek-language applications\, including public-service information
  retrieval and conversational assistance. \n	\n\n\n\n\n\n	\n	The skills 
 to analyse\, evaluate and improve RAG systems for real-world deployment 
 \n	\n\n\n\nInstructors' profiles:\n\n\n	George Drosatos\, ATHENA RC\n\n\n
 George Drosatos is a Principal Researcher\, Researcher Grade B\, at the In
 stitute for Language and Speech Processing of the Athena Research Center\,
  with expertise in privacy technologies\, information retrieval\, content 
 analysis\, information security and biomedical informatics. He holds a Dip
 loma\, MSc and PhD in Electrical and Computer Engineering from Democritus 
 University of Thrace. He has participated in more than 20 national and Eur
 opean research projects and has extensive teaching experience in undergrad
 uate and postgraduate courses at Greek and international universities. His
  research focuses on privacy-enhancing technologies\, secure data analysis
 \, trustworthy AI and data-driven systems. He has authored more than 76 pu
 blications\, with over 1\,800 citations\, h-index 23 and i10-index 37. He 
 has also served as Guest Editor in multiple Special Issues and as Secretar
 y General of EAMBES from 2023 to 2025. \n\nMore information: https://www.d
 rosatos.info.\n\n\n	Sotiris Gyftopoulos\, ATHENA RC\n\n\nSotiris Gyftopou
 los is a Scientific Associate at the Institute for Language and Speech Pro
 cessing (ILSP) of the Athena Research Center. He holds a degree in Compute
 r Science from the University of Crete and a PhD from the Department of El
 ectrical and Computer Engineering at Democritus University of Thrace\, wit
 h his doctoral research focusing on influence analysis in social networks.
  His expertise lies at the intersection of Natural Language Processing (NL
 P)\, statistical data analysis and social network modelling. With extensiv
 e experience in national and European research projects\, Dr Gyftopoulos h
 as also taught graduate-level courses on data analysis and database system
 s. His scientific work has been published in international journals and co
 nference proceedings\, with emphasis on information diffusion and influenc
 e analysis through stochastic processes and advanced machine learning tech
 niques.\n\n \n\nNote: Please enter your institutional/corporate email whe
 n registering.\n\nhttps://events.grnet.gr/event/213/
LOCATION:
URL:https://events.grnet.gr/event/213/
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