BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Data Science Initiative - ECPv6.3.7//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Data Science Initiative
X-ORIGINAL-URL:https://datascience.uci.edu
X-WR-CALDESC:Events for Data Science Initiative
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20170312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20171105T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170203T090000
DTEND;TZID=America/Los_Angeles:20170203T170000
DTSTAMP:20260403T192315
CREATED:20170117T111019Z
LAST-MODIFIED:20170117T111019Z
UID:2019-1486112400-1486141200@datascience.uci.edu
SUMMARY:Predictive Modeling with Python
DESCRIPTION:Learn about the use of predictive models in Python through scikit-learn.\n \nPython is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification settings will be considered. The course will be taught mostly through the medium of iPython notebooks. \nThis course is targeted primarily at graduate students who have not already taken a full course in machine learning. \nDate: February 3\, 2017 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Preston Hinkle\, John Schomberg\, Brian Vegetabile\, UC Irvine \nPre-requisites: basic familiarity with Python (prior experience with scikit-learn is not necessary). To understand the more theoretical aspects of the course\, it is recommended to have knowledge of linear algebra\, probability\, and calculus. \nLearning Materials:https://github.com/UCIDataScienceInitiative/PredictiveModeling_withPython
URL:https://datascience.uci.edu/event/predictive-modeling-python-020317/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170216T130000
DTEND;TZID=America/Los_Angeles:20170217T173000
DTSTAMP:20260403T192315
CREATED:20170111T110214Z
LAST-MODIFIED:20170111T110214Z
UID:1992-1487250000-1487352600@datascience.uci.edu
SUMMARY:Workshop on Big Data in Brain Science
DESCRIPTION: \nThe Data Science Initiative is sponsoring a two-day workshop on February 16 and 17 highlighting recent advances on big data in brain science. The event will consist of tutorials on Feb 16 and presentations & discussions on the scientific context and data/analytic/modeling strategies on Feb 17.  \nDate and Time \nFebruary 16: 1:00 p.m. to 5:30 p.m.\nFebruary 17: 8:30 a.m. to 5:30 p.m. \nLocation: Calit2 Auditorium\, UCI. Parking is $10 in the Anteater Parking Structure (directions) \n \nThe event is free and open to the public.\nInvite your friends on Facebook.  \nThursday\, February 16\, 2017 \n\n\n\n\nTime                   \nDescription\n\n\n\n\n1:00 – 3:15 p.m.\nTutorial on Pre-Processing of fMRI Data\nMark Fiecas\, Ph.D.\, Assistant Professor\, Department of Biostatistics\, University of Minnesota\n\n\n3:15 – 3:45 p.m.   \nCoffee Break\n\n\n3:45 – 5:30 p.m.\nTutorial on Pre-Processing of EEG Data (EEGLAB)\nScott Makeig\, Ph.D.\, Research Scientist & Director\, Swartz Center for Computational Neuroscience\, University of California\, San Diego\n\n\n\n\nFriday\, February 17\, 2017\n\n\n\n\nTime                   \nDescription\n\n\n\n\n8:30 – 8:45 a.m.\nWelcome and Introduction\nPadhraic Smyth\, Ph.D.\, Director\, Data Science Initiative\nProfessor of Computer Science and Professor of Statistics\, UCIHernando Ombao\, Ph.D.\, Co-Organizer\nProfessor of Statistics and Professor of Cognitive Sciences\n\n\nSession 1\nData Analytic Challenges in Neural Signals (spike train\, LFP)\nModerator: Babak Shahbaba\, Associate Professor of Statistics\, UCI\n\n\n8:45 – 9:15 a.m.\nEllen Wann\nGraduate Student\, Frostig Lab\nCenter for the Neurobiology of Learning and Memory\, UCI\n\n\n9:15 – 9:45 a.m.   \nChi-Wing Ng\nPost-doctoral Researcher\, Fortin Lab\nCenter for the Neurobiology of Learning and Memory\, UCI\n\n\n9:45 – 10:15 a.m.\nSam Behseta\nProfessor of Mathematics and Statistics\, Cal State Fullerton \n\n\n10:15 – 10:45 a.m.   \nDiscussion (led by Prof. Shahbaba)\n\n\n10:45 – 11:15 a.m.  \nCoffee Break\n\n\nSession 2\nData Analytic Challenges in fMRI\n Moderator: Michele Guindani\, Associate Professor of Statistics\, UCI\n\n\n11:15 – 11:45 a.m.   \nZach Reagh\nGraduate Student\, Yassa Lab\nDepartment of Neurobiology and Behavior\, UCI\n\n\n11:45 – 12:15 p.m.\nRon Frostig\, Ph.D.\nProfessor of Neurobiology and Behavior\, UCI\n\n\n12:15 – 12:45 p.m.   \nJessica Cassidy\nPost-doctoral Researcher\, Cramer Lab\nDepartment of Anatomy and Neurobiology\, UCI\n\n\n1245 – 1:15 p.m.\nDiscussion (led by Prof. Guindani)\n\n\n1:15 – 2:15 p.m.   \nLunch Break\n\n\nSession 3\nData Analytic Challenges in EEG\n Moderator: Ramesh Srinivasan\, Professor and Chair of Cognitive Sciences\, UCI\n\n\n2:15 – 2:45 p.m.   \nDaniel Shrey\, M.D.\nPediatric Neurology\, CHOC\n\n\n2:45 – 3:15 p.m.\nRachel Smith\nGraduate Student\, Lopour Lab\nLaboratory of Computational and Translational Neuroscience\nDepartment of Biomedical Engineering\, UCI \n\n\n3:15 – 3:45 p.m.   \nDustin Pluta\nGraduate Student\, Space-Time Group and Statistical Genetics\nDepartment of Statistics\, UCI\n\n\n3:45 – 4:15 p.m.\nAnirudh Wodeyar\nGraduate Student\, Srinivasan Lab\nDepartment of Cognitive Sciences\, UCI\n\n\n4:15 – 4:45 p.m.   \nDiscussion (led by Prof. Srinivasan)
URL:https://datascience.uci.edu/event/workshop-on-big-data-in-brain-science/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170216T133000
DTEND;TZID=America/Los_Angeles:20170217T173000
DTSTAMP:20260403T192315
CREATED:20170214T103912Z
LAST-MODIFIED:20170214T103912Z
UID:2278-1487251800-1487352600@datascience.uci.edu
SUMMARY:Big Data in Brain Science Workshop
DESCRIPTION:    \nBig Data in Brain Science Workshop\n \nThe Data Science Initiative is sponsoring a two-day workshop on February 16 and 17 highlighting recent advances on big data in brain science. The event will consist of tutorials on Feb 16 and presentations & discussions on the scientific context and data/analytic/modeling strategies on Feb 17. \nDate: February 16 -17\, 2017\nTime: February 16 1:30 pm  – February 17 5:30 p.m.\nLocation: Calit2 Auditorium\, UCI. Parking is $10 in the Anteater Parking Structure (directions) \nThis event has passed. \n \nLet people know you are going to this event.\nInvite your friends on Facebook. \nhttps://www.facebook.com/uci.datascience/videos/1781228885452303/ \nhttps://www.facebook.com/uci.datascience/videos/1781222048786320/
URL:https://datascience.uci.edu/event/big-data-brain-science-workshop/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170221T090000
DTEND;TZID=America/Los_Angeles:20170221T170000
DTSTAMP:20260403T192315
CREATED:20170123T215355Z
LAST-MODIFIED:20170123T215355Z
UID:2033-1487667600-1487696400@datascience.uci.edu
SUMMARY:Topics in R
DESCRIPTION:This course builds on our Introduction to R by teaching advanced visualization and data tidying.\n \nIn this course\, you will cover advanced visualization including ggplot and R Shiny. In addition to visualizations\, principles of tidy data and reporting will be discussed. \nDate: February 21\, 2017 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Linnge Li\, Dustin Pluta\, UC Irvine \nPre-requisites: 1) familiarity with basic statistical concepts\, and 2) intermediate R programming knowledge. For the tutorial\, bring a laptop with R downloaded and installed and WiFi.
URL:https://datascience.uci.edu/event/topics-in-r-022117/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR