BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Graph Massivizer EU Project - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://graph-massivizer.eu
X-WR-CALDESC:Events for Graph Massivizer EU Project
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20230101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240720
DTEND;VALUE=DATE:20240729
DTSTAMP:20260419T150051
CREATED:20240410T123124Z
LAST-MODIFIED:20240410T124219Z
UID:891-1721433600-1722211199@graph-massivizer.eu
SUMMARY:Data Science International Summer School
DESCRIPTION:Organized by  Bucharest University of Economic Studies  in collaboration with the  GATE Institute at Sofia University “St. Kliment Ohridski” and the projects  enRichMyData \,  Graph-Massivizer \,  UPCAST \,  INTEND \, and  InterTwino \,  The goal of this 5th edition of the Summer School is to familiarize participants with relevant state of the art topics in data science and artificial intelligence (AI). The program will cover fundamentals of data science and AI and focus on the following key topics: • Data analytics and statistics • Machine learning and deep learning • Large Language Models and Conversational AI • Causal AI • Time series and graph data • Data sharing • Data and AI pipelines The location where the course will be held is the beautiful town of Predeal\, located in the Transylvania region in Romania\, famous for its mountain landscapes and natural and historical attractions. Register  here  and see you in Predeal!
URL:https://graph-massivizer.eu/events/data-science-international-summer-school/
LOCATION:Predeal\, Romania
CATEGORIES:AI,DataScience,Graphs,KnowledgeGraphs,Sustainable Graph,Sustainable Graph Processing Systems
ATTACH;FMTTYPE=image/png:https://graph-massivizer.wp.itec.aau.at/wp-content/uploads/sites/27/2024/04/Screenshot-2024-04-10-alle-10.25.11.png
END:VEVENT
END:VCALENDAR