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X-WR-CALNAME:Data Science Initiative
X-ORIGINAL-URL:https://datascience.uci.edu
X-WR-CALDESC:Events for Data Science Initiative
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DTSTART:20160313T100000
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161003T090000
DTEND;TZID=America/Los_Angeles:20161003T170000
DTSTAMP:20260404T212635
CREATED:20160926T183542Z
LAST-MODIFIED:20160926T183542Z
UID:1877-1475485200-1475514000@datascience.uci.edu
SUMMARY:Intro to Linux on the HPC
DESCRIPTION:This course is for researchers who have never used Linux and/or a computer cluster and introduces concepts and best practices for both. \n \nDescription: \n \nThis course covers how to best exploit the bash shell for both interactive work and batch jobs\, moving & simple manipulation of data\, as well very short introductions to programming in bash\, Perl\, and R. This is not computer science; this is a driver’s license. \nDate:October 3\, 2016\nTime: 9 a.m. to 5 p.m. with lunch provided\nLocation: Donald Bren Hall\, Room 3011\nInstructor: Harry Mangalam\, OIT/HPC\, UC Irvine\nPre-requisites: For the course\, none. For the tutorial\, a laptop with WiFi\, with a terminal application (Macs have the Terminal app; Windows need putty)\, and both would benefit from ‘x2go’. \n 
URL:https://datascience.uci.edu/event/intro-to-linux-on-the-hpc/
LOCATION:Donald Bren Hall 3011
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=image/jpeg:https://datascience.uci.edu/wp-content/uploads/2014/09/8450190120_ebcf41863d_o.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161007T090000
DTEND;TZID=America/Los_Angeles:20161007T170000
DTSTAMP:20260404T212635
CREATED:20160929T151518Z
LAST-MODIFIED:20160929T151518Z
UID:1887-1475830800-1475859600@datascience.uci.edu
SUMMARY:Introduction to R
DESCRIPTION:This course provides an introduction to the fundamentals of the R language and its applications to data analysis. \n \nIn this course\, you will learn how to program in R and how to effectively use R for data analysis. The course covers an introduction to data/object types in R\, reading data\, creating data visualizations\, accessing and installing R packages\, writing R functions\, fitting statistical models including regression models and performing statistical tests including t-tests and ANOVA. Practical examples will be provided during the course. \nDate:October 7\, 2016 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Emma Smith\, Steven Brownlee\, UC Irvine \nPre-requisites: 1) familiarity with basic statistical concepts\, and 2) basic programming knowledge. For the tutorial\, bring a laptop with R downloaded and installed and WiFi. \nTeaching material repository:https://github.com/UCIDataScienceInitiative/IntroR_Workshop
URL:https://datascience.uci.edu/event/introduction-to-r-8/
CATEGORIES:Data Science Event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161007T150000
DTEND;TZID=America/Los_Angeles:20161007T183000
DTSTAMP:20260404T212635
CREATED:20160912T105453Z
LAST-MODIFIED:20160912T105453Z
UID:1871-1475852400-1475865000@datascience.uci.edu
SUMMARY:Symposium on Recent Advances in Data Science
DESCRIPTION:The Data Science Initiative is sponsoring a short symposium highlighting recent advances in data science. The event will consist of talks on a variety of topics related to data science followed by a reception and graduate student poster session\, including posters from the 2016 Data Science Summer Fellows. \nDate: October 7\, 2016\nTime: 3:00 – 6:30 p.m.\nLocation: Calit2 Auditorium (directions) \nThis event has passed. \n>> View photos from the event. \nSchedule: \n\n\n\n\nTime\nDescription\n\n\n\n\n3:00 p.m.\nUpdate on data science at UCI\nPadhraic Smyth\, Director\, UCI Data Science Initiative\n\n\n3:20 p.m.\nResearch Highlight: Interpreting machine learning predictions\nSameer Singh\, Assistant Professor\, Department of Computer Science\, UCI\n\n\n3:50 p.m.\nResearch Highlight:  A Bayesian perspective on publication bias in the Reproducibility Project: Psychology\nJoachim Vandekerckhove\, Associate Professor\, Department of Cognitive Sciences\, UCI\n\n\n4:20 p.m.\nInvited Keynote: Google data and public sentiment\nDr. Steve Scott\, Senior Economic Analyst\, Google\n\n\n5:00 p.m.\nReception and graduate student poster session\n\n\n\n\n[/two_third][one_third spacing=”yes” last=”yes” center_content=”no” hide_on_mobile=”no” background_color=”” background_image=”” background_repeat=”no-repeat” background_position=”left top” link=”” hover_type=”none” border_position=”all” border_size=”0px” border_color=”” border_style=”solid” padding=”” margin_top=”” margin_bottom=”” animation_type=”0″ animation_direction=”down” animation_speed=”0.1″ animation_offset=”” class=”” id=””] \n \nSubmit a Poster\nUCI graduate students are invited to submit applications to present at the poster session on current and research projects that have a significant data science component\, e.g.\, research in areas such as machine learning\, statistics\, databases\, data privacy\, visualization as well as research on domain-specific topics in the sciences and humanities that have a strong data-driven component. \n  \nDeadline has passed[/one_third]
URL:https://datascience.uci.edu/event/academic-year-kickoff-event-advances-in-data-science/
CATEGORIES:Data Science Event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161014T160000
DTEND;TZID=America/Los_Angeles:20161014T170000
DTSTAMP:20260404T212635
CREATED:20161006T130029Z
LAST-MODIFIED:20161006T130029Z
UID:1895-1476460800-1476464400@datascience.uci.edu
SUMMARY:Information Session on the Insight Data Science Fellows Program
DESCRIPTION:Information Session on the Insight Data Science Fellows Program\nSpeaker: Emily Thompson\, Insight Data Science\,  insightdatascience.com\nTarget audience: Graduate students and Postdoctoral researchers \nDate: Friday\, October 14\nTime: 4:00 to 5:00 p.m.\nLocation: Calit2 Auditorium\, UCI (directions) \n[button link=”https://uci-oai.formstack.com/forms/insight_info_101416″ color=”default” size=”” stretch=”” type=”” shape=”” target=”_self” title=”” gradient_colors=”|” gradient_hover_colors=”|” accent_color=”” accent_hover_color=”” bevel_color=”” border_width=”1px” icon=”” icon_divider=”yes” icon_position=”left” modal=”” animation_type=”0″ animation_direction=”down” animation_speed=”0.1″ animation_offset=”” alignment=”left” class=”” id=””]RSVP Today[/button][separator style_type=”none” top_margin=”10″ bottom_margin=”10″ sep_color=”” border_size=”” icon=”” icon_circle=”” icon_circle_color=”” width=”” alignment=”center” class=”” id=””]\nAbout Emily Thompson \nEmily Thompson\, Product Manager at Insight Data Science\, will be talking about her transition from academia to the field of data science. She will also be leading a discussion on careers in data science\, health data science\, and data engineering\, and steps you can take towards these career paths. Top companies are hiring data scientists and engineers to help find insights in the petabytes of data that they collect every day. Scientists and engineers from diverse fields\, including computational biology\, neuroscience\, math\, and statistics are playing key roles in transforming the way of working with data to impact our daily lives. \n  \nAbout Insight Fellows Program\nThe Insight Fellows Program is a training fellowship designed to bridge the gap between academia and a career in data science or data engineering. Insight provides seven-week\, full-time\, training fellowships in Silicon Valley\, New York\, and Boston. We offer a full tuition scholarship\, dedicated office space\, and project-based learning under the guidance of top industry mentors. Over 600 Insight alumni are now working at Facebook\, Apple\, LinkedIn\, Twitter\, Reddit\, Netflix\, NBC\, MTV\, Khan Academy\, Biogen and other top companies.\nIn this info session\, we will provide a high-level overview of data science and engineering in industry and describe the Insight Fellows Program. The Program is open to individuals from all subjects working on quantitative data analysis (our Data Science and Health Data Science Programs have a PhD requirement). The session will also include time for Q&A. Learn more at: insightdatascience.com
URL:https://datascience.uci.edu/event/information-session-on-the-insight-data-science-fellows-program-2/
CATEGORIES:Data Science Event
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DTSTART;TZID=America/Los_Angeles:20161020T090000
DTEND;TZID=America/Los_Angeles:20161020T170000
DTSTAMP:20260404T212635
CREATED:20161008T162053Z
LAST-MODIFIED:20161008T162053Z
UID:1906-1476954000-1476982800@datascience.uci.edu
SUMMARY:Next Generation Sequencing Data Analysis
DESCRIPTION:This course provides an introduction to the basics of using open source software tools to analyze large scale genomics data\, specifically Next Generation Sequencing data.\n \nIn this course\, you will learn general NGS workflow\, data analysis pipeline\, data formats\, short read mapping and alignment software\, general workflow for DNA-seq\, RNA-seq and ChIP-seq. Data visualization tools will also be covered. Single Cell RNA-seq will be discussed. \nDate:October 20\, 2016 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Jenny Wu\, UC Irvine \nPre-requisites: Some programming experience is recommended. For the tutorial\, bring a laptop with wifi and is pre-registered with the UCI Mobile network with a free HPC account. For Windows users\, please install the “putty” terminal program (PuTTY) and the Windows x2go client (x2go). \nLearning Materials:http://ghtf.biochem.uci.edu/content/ngs-data-analysis
URL:https://datascience.uci.edu/event/next-generation-sequencing-data-analysis/
CATEGORIES:Data Science Event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161025T090000
DTEND;TZID=America/Los_Angeles:20161025T170000
DTSTAMP:20260404T212635
CREATED:20161008T164036Z
LAST-MODIFIED:20161008T164036Z
UID:1907-1477386000-1477414800@datascience.uci.edu
SUMMARY:A Deep Introduction to Julia
DESCRIPTION:This workshop aims to introduce both users of scripting languages and advanced programmers to the Julia ecosystem and explore details about the Julia language which can help produce efficient and readable code.\n \nThe goal of the workshop is for students to understand where Julia can be applied and be well-equipped to start using Julia in their own research. Students will learn about the current state of Julia development (IDEs\, documentation\, where to get help)\, how to write efficient code by understanding some of Julia’s internals via small projects\, solve problems using advanced Julia features (metaprogramming\, multiple-dispatch\, etc.)\, and learn workarounds to common issues newcomers face (scoping problems\, type conversions\, etc.). \nDate:October 25\, 2016 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Chris Rackauckas\, UC Irvine \nPre-requisites: Solid understanding of programming. Installing Julia beforehand is not required\, though highly recommended. Attendees may wish to install the Julia/Atom IDE before the workshop\, though be advised this may not be easy (instructions). Help for doing so can be found at the UCI Data Science Initiative Gitter and the JunoLab Gitter. \nMaterials Repository:https://github.com/UCIDataScienceInitiative/IntroToJulia
URL:https://datascience.uci.edu/event/a-deep-introduction-to-julia/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=image/jpeg:https://datascience.uci.edu/wp-content/uploads/2014/12/DSC00932.jpg
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