BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260705T185718Z UID:c52bdbb0-29e0-4e6d-a4de-f1a5f4f899f5 DTSTART:20180206T083000Z DTEND:20180209T153000Z DESCRIPTION:Registration will open in December. Please\, bring your own lap top. All the PATC courses at BSC are free of charge.\n\nCourse Convener:   Maria-Ribera Sancho\n\nObjectives: The course brings together key infor mation technologies used in manipulating\, storing\, and analysing data in cluding:\n\nthe basic tools for statistical analysis\n techniques for para llel processing\n tools for access to unstructured data\n storage solution s\nLearning outcomes: Students will be introduced to systems that can acce pt\, store\, and analyse large volumes of unstructured data. The learned s kills can be used in data intensive application areas.\n\nLevel: For train ees with some theoretical and practical knowledge\n\nAGENDA:  \n\nay 1 06 /02:  \n \n\n 9:30 – 13:00 Introduction (Vassil Alexandrov)\n\nData S cience current trends session will focus on results of the latest key stud ies both in Europe and the USA in the area of Data Science and will outlin e the major trends\, findings and recommendations.\nCoffee break 11:00- 11 :30\n\nData Science definitions and mathematical foundations introduction. \nWhile tackling Big Data problems in many cases elementary or standard st atistical approaches fail. New research methods are required to be develop ed to tackle such problems. Therefore this session will focus key research methods and approaches for Data Science\, ranging from theory creating an d theory testing approaches to conceptual-analytical approaches and experi mental ones\, that are able to lead to discovering global properties on da ta. These will be mainly deterministic and hybrid (stochastic/deterministi c) methods and algorithms.\n \n\n14:00 – 16:00\n\nThis session will foc us on several key methods and algorithms (both serial and parallel) that e nable to discover global properties on data while dealing with Big Data:\n Network Science\n Multi Constrained and Multi-Objective Optimization\n Examples of using the above approaches\n \n Examples using the above appro aches and some hands-on exercise\nCoffee break 16:00 – 16:30 \n\nSocial Simulation Applications  (Josep Casanovas)\n---------------------------- -------------------------------------------------------------------------- -Day 2 07/02: \n\n 9:30 – 13:00 (Josep Lluis Berral)\n\nData Analytics with Apache Spark.\nApache Spark has become a consolidated technology for large-scale processing in a fast and general way\, with “programmer-frie ndly” interfaces and official bindings for many of the most used languag es (Java\, Scala\, Python and R)\, extensive documentation and development tools. This course introduces Apache Spark\, as well as some of its core libraries for data manipulation\, machine learning\, data streams and grap h analytics.\n\nCoffee break 11:00- 11:30\n \n\n 14 :00 – 16 :00\n\nDa ta Analytics with Apache Spark. Part 2\nCoffee break 16:00 – 16:30\n\n  \n\nBig IoT Project (Dr. Ernest Teniente)\n  \n-------------------------- -------------------------------------------------------------------------- ---Day 3 8/02\n\n9:30 – 13:00 (Albert Abelló and Petar Jovanovic)\n\nBi g Data Management: Big Data has many definitions and facets\, we'll pay a ttention to the problems we have to face to store it and how we can proces s it. More specifically\, we'll focus on the Apache Hadoop ecosystem and i ts two basic components\, namely HBase and MapReduce engine.\nCoffee break 11:00- 11:30\n\nHands-on exercise\n 14:00-16:00 (Rizkallah Touma)\n\nNo SQL databases: The relational model has dominated data storage systems sin ce the mid 1970s. However\, the changing storage needs over the past decad e have given rise to new models for storing data\, collectively known as N oSQL. In this presentation\, we will focus on two of the most common types of NoSQL databases: document-oriented databases and graph databases and e xplain the use cases suitable for each of them.\n  \nCoffee break 16:00 - 16:30\n\n 16:30-18:00 (Dr. Maria Cristina Marinescu)\n\nMultidisciplina ry research and data analytics: Smart Cities\n---------------------------- -------------------------------------------------------------------------- -\n\nDay 4 09/02: \n\n 9:30 – 11:30 (Dr. Darío García) \n\nIntroducti on to Deep Learning\nCoffee break 11:30- 12:00\n\n \n\n12:00 – 13.00 (D r. Javier Espinosa)\n\nData visualizations are everywhere and are more imp ortant than ever. From creating a visual representation of data points as part of an executive presentation\, to showcasing progress\, or visualizin g concepts for customer segments\, data visualizations are a critical and valuable tool in many different situations. When it comes to big data\, we ak tools with basic features do not cut it so specific techniques should b e applied. This course will address different techniques for visualizing b ig data collections including a vision of the visualization process as a c omplex and greedy task and then as out of the box solution that can help t o analyze and interpret big data collection.\nCoffee break 11:00- 11:30\n\ n 14:00– 18:00 \n\nHands-on Exercise\nCoffee break 16:00 – 16:30\n\nH ands-on Exercise\nEND of COURSE\n\n \n\nhttps://events.prace-ri.eu/event/ 649/ SUMMARY:Big Data Analytics @ BSC URL;VALUE=URI:https://events.prace-ri.eu/event/649/ END:VEVENT END:VCALENDAR