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X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200724T140000
DTEND;TZID=America/Detroit:20200724T160000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20230905T171251Z
UID:10000379-1595599200-1595606400@micde.umich.edu
SUMMARY:Geostatistics – II
DESCRIPTION:In many situations\, we observe a process over a limited number of locations and are interested in estimating its values at nearby unsampled locations. Geostatistical methods provide a powerful tool to do this. In this session\, we will build upon the material and intuitions covered in the first workshop. We will focus on the principles\, application\, and interpretation of results using R\, and will cover topics such as variogram modeling\, empirical variogram\, estimation techniques\, and prediction uncertainty. \n\nYou should be familiar with R and the basic concepts of GIS data\, should have taken an introductory course in statistics\, and know the basics of linear algebra.
URL:https://micde.umich.edu/event/geostatistics-ii/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200720T130000
DTEND;TZID=America/Detroit:20200720T160000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20230905T171251Z
UID:10000367-1595250000-1595260800@micde.umich.edu
SUMMARY:Wear OS: Creating A Watchface For Your Android Smartwatch
DESCRIPTION:A BlueJeans link will be sent to all registered participants. \nSmartwatches are multi-functional devices that can be worn on the wrist. They can read your heartbeat\, notify you of messages from your phone\, and can even tell the time! Google’s “Wear OS” is a branch of the Android mobile operating system\, and it encourages open app development. \nThis is the first of two workshops to introduce programming for a Wear OS watch. This will introduce some of the functions of a smartwatch\, through the programming and design of a new watchface. Participants will learn how to design a custom watchface using Java and Android Studio\, with a step-by-step example.
URL:https://micde.umich.edu/event/wear-os-creating-a-watchface-for-your-android-smartwatch/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200715T140000
DTEND;TZID=America/Detroit:20200715T160000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20260401T202047Z
UID:10000380-1594821600-1594828800@micde.umich.edu
SUMMARY:Efficient Data Exploration
DESCRIPTION:Tired of using `table` and `summary`?  Or repeatedly using a `group_by %>% summarise` approach?  Many are still using R inefficiently to summarize data\, especially for presentation. However\, data needs to be explored before modeling can take place\, both to familiarize oneself with the strengths and limitations of the data\, as well as to diagnose errors or spot potential problems that might arise.  So how can we do this sort of thing better?\n\nThis workshop will demonstrate the capabilities of several packages that might be of interest to those seeking a more automatic way to summarize their data before analysis\, or simply to share with others.
URL:https://micde.umich.edu/event/efficient-data-exploration/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200714T140000
DTEND;TZID=America/Detroit:20200714T163000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20230905T171251Z
UID:10000370-1594735200-1594744200@micde.umich.edu
SUMMARY:Introduction to Python's NumPy library
DESCRIPTION:A BlueJeans link will be sent to all registered participants.\n\nThis workshop will introduce you to the NumPy library in Python\, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth\, along with related linear algebra and random number capabilities. Some familiarity with Python is expected. \nThe workshop will be done online via BlueJeans. We will run the code using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/introduction-to-pythons-numpy-library-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200706T140000
DTEND;TZID=America/Detroit:20200706T160000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20230905T171251Z
UID:10000378-1594044000-1594051200@micde.umich.edu
SUMMARY:Mapping tools for COVID-19 data – II
DESCRIPTION:This is the second workshop in this series and will build on the material and the techniques covered in the first workshop. We will use COVID-19 data available here https://github.com/nytimes/covid-19-data\, combine it with other data such as from Census and will learn about creating maps\, including web maps\, that involve more than one variable. \n\nWe will use R and QGIS. You should know the basics of vector data GIS and introductory techniques of classification and clustering\, be a regular R user\, and should have some familiarity with QGIS.
URL:https://micde.umich.edu/event/mapping-tools-for-covid-19-data-ii/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200616T140000
DTEND;TZID=America/Detroit:20200616T163000
DTSTAMP:20260604T013120
CREATED:20230905T171251Z
LAST-MODIFIED:20230905T171251Z
UID:10000369-1592316000-1592325000@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:A BlueJeans link will be sent to all registered participants. \nDeep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. \nThe workshop will be done online via BlueJeans. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-6/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200615T130000
DTEND;TZID=America/Detroit:20200615T150000
DTSTAMP:20260604T013120
CREATED:20230905T171250Z
LAST-MODIFIED:20230905T171250Z
UID:10000366-1592226000-1592233200@micde.umich.edu
SUMMARY:SRTI: Software For Cross-Language Real-Time Data Communication
DESCRIPTION:A BlueJeans link will be sent to all registered participants. \nComputer software simulation is used in virtually every discipline. These programs virtually represent small components of real-world events and behaviors\, and allow scientists to test different models to guide real-world research. However\, these can be individually complex\, and written in different computer languages and programs. It’s a difficult task to combine simulators from different parts of a research team to represent larger systems. \nThe “Simple Run-Time Infrastructure” is an open-source\, free-to-use software tool\, developed at the University of Michigan. It was built to simplify the process of sharing data between multiple live simulators\, using a “publish/subscribe” model with messages rather than directly to specific programs. This workshop will present the background of the SRTI’s development\, what it is capable of\, and will provide a step-by-step example for participants. \nJava will be required to run the SRTI. The example will use an optional mixture that includes simulators written in Java\, Matlab\, and Python.
URL:https://micde.umich.edu/event/srti-software-for-cross-language-real-time-data-communication/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200610T140000
DTEND;TZID=America/Detroit:20200610T160000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000377-1591797600-1591804800@micde.umich.edu
SUMMARY:R IV: Visualization
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register.\n\nVisualizing the results of research is a key aspect in facilitating scientific communication to a broad audience. The focus of this workshop will be on using common tools in R for visualization\, general concerns in producing visual information\, and demonstration of approaches that allow for interactivity.\n\n\nPrereq: Some experience using R is required (R I\, preferably R II workshops)\, as well as exposure to basic statistical analysis would be beneficial.\n\n\nContent: http://m-clark.github.io/data-processing-and-visualization/
URL:https://micde.umich.edu/event/r-iv-visualization/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200608T140000
DTEND;TZID=America/Detroit:20200608T163000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000365-1591624800-1591633800@micde.umich.edu
SUMMARY:Mapping tools to visualize COVID19 data
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register.\n\nThis workshop will help you learn the approaches and tools to visualize spatial data using R and QGIS. We will use the COVID19 data available at (https://github.com/nytimes/covid-19-data) and combine it with information from Census and other sources to visualize spatial patterns and make production quality maps.\n\nParticipants should have some exposure to R and vector data GIS.
URL:https://micde.umich.edu/event/mapping-tools-to-visualize-covid19-data/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200601T150000
DTEND;TZID=America/Detroit:20200601T170000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000376-1591023600-1591030800@micde.umich.edu
SUMMARY:CSCAR/MIDAS Workshop on Data\, Methodology\, and Covid
DESCRIPTION:Zoom link:  https://umich.zoom.us/j/99072338239 \n  \nThe second CSCAR/MIDAS workshop on Data\, Methodology\, and Covid will focus on Covid testing and mortality data from the Covid Tracking Project (covidtracking.com) and Worldometer (worldometer.com).  We will develop insight into how the reported PCR testing data from various US states\, and from different countries\, can be informative about Covid deaths in those localities.  We will also discuss some of the challenges of estimating the “infection fatality ratio” with this type of data\, and conduct some sensitivity analyses to see what the IFR would be in different settings. \nThe workshop will use intermediate statistical methods (to be reviewed in the workshop)\, and computations will be done in Python.  Notebooks and links to data will be provided.
URL:https://micde.umich.edu/event/cscar-midas-workshop-on-data-methodology-and-covid/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200529T130000
DTEND;TZID=America/Detroit:20200529T160000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000373-1590757200-1590768000@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; workflow scripting using bash; high-throughput computing using launcher; parallel processing in one or more of Python\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nMPI Profiling with Allinea MAP\nGreat Lakes Slurm HPC cluster\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Flux user login\, you don’t need to do anything.  Otherwise\, go to the Flux user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.\nDownload and install PuTTY directly from the developer.Our Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes.\n\nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200528T100000
DTEND;TZID=America/Detroit:20200528T130000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000372-1590660000-1590670800@micde.umich.edu
SUMMARY:Research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW \nThis workshop will provide a brief overview of the components of the Great Lakes Cluster. The main body of the workshop will cover the resource manager and scheduler\, creating submissions scripts to run jobs and the options available in them\, and hands-on experience. By the end of the workshop\, every participant should have created a submission script\, submitted a job\, tracked its progress\, and collected its output. Participants will have several working examples from which to build their own submissions scripts in their own home directories. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMark Champe\nResearch Computing Services\nLSA Technology Services \nMATERIALS\nLecture notes\nGreat Lakes HPC cluster \nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you don’t already have a Great Lakes user login\, please visit the application page. \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \nLAPTOP PREPARATION \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.\nDownload and install PuTTY directly from the developer.Our Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes.\nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \nA Zoom link will be provided to the participants the day before the class. Registration is required.
URL:https://micde.umich.edu/event/research-computing-on-the-great-lakes-cluster-10/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200527T130000
DTEND;TZID=America/Detroit:20200527T160000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000374-1590584400-1590595200@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \nINSTRUCTOR \nKenneth Weiss\nIT Project Senior Manager \nHITS Academic IT – HPC team \nKen is a High Performance Computing Consultant with the Health Information Technology & Services (HITS) Academic IT – HPC team at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMATERIALS \n\nLecture Notes\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCOURSE PREPARATION \nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems. \nIf you do not have this software already\, please download and install the Cisco AnyConnect VPN software following these instructions: https://its.umich.edu/enterprise/wifi-networks/vpn/getting-started You will need this to be able to use the ssh client. You will need to use the ‘Campus All traffic’ profile in the Cisco client. \nYou will need an ssh client to connect to the training host. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n· Download and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer. \n· Download and install PuTTY directly from the developer. \nDuring class you will be given the name of the training host to be able to participate in the hands-on activities. \nA Zoom link will be provided to the participants the day before the class. Registration is required. \nInstructor will be available at the Zoom link\, to be provided\, from 12-1 PM for computer setup assistance. \n\nIf you have questions about this workshop\, please send an email to the instructor at kgweiss@umich.edu
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-12/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200518T150000
DTEND;TZID=America/Detroit:20200518T170000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000368-1589814000-1589821200@micde.umich.edu
SUMMARY:CSCAR/MIDAS workshops on data\, methodology\, and Covid
DESCRIPTION:CSCAR and MIDAS will hold a series of on-line technical workshops on the use of publicly-available data for analyzing human health at the population level. Some of the analyses and data are relevant to understanding the covid pandemic\, but the focus of these workshops is on methods that are of broader use in population health research. Participants will gain practical skills in using intermediate methods from statistics and data science to gain meaningful insights from various types of data. Python code and links to all relevant data will be provided for each workshop. The first workshop in this series will be held on May 18th from 3-5pm\, and will cover the use of generalized linear modeling and generalized PCA to gain insight into mortality trends among various demographic subgroups in the United States\, using data from the CDC.
URL:https://micde.umich.edu/event/cscar-midas-workshops-on-data-methodology-and-covid/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200515T130000
DTEND;TZID=America/Detroit:20200515T153000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000362-1589547600-1589556600@micde.umich.edu
SUMMARY:Spatial Point Process Modelling in R
DESCRIPTION:A BlueJeans link will be sent to all registered participants.\n\nSpatial point process models help us analyze the geometrical pattern of points (events) in space and find application in a variety of fields including image processing\, public health\, forestry\, ecology\, and business. This workshop will provide an introduction to point process models focusing on the conceptual aspects and implementation in R.\n\nThe concepts and techniques transfer naturally to similar problems in 1-D (e.g. events in time). So\, the workshop will also be useful for participants who want to learn about analysis of random events in time.
URL:https://micde.umich.edu/event/spatial-point-process-modelling-in-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200505T090000
DTEND;TZID=America/Detroit:20200505T113000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000363-1588669200-1588678200@micde.umich.edu
SUMMARY:Intro to SQL
DESCRIPTION:Ever want to know how to communicate with a database? You need to know SQL\, a standard programming language for working with relational database management systems in data warehouses or just Microsoft Access. This workshop will cover the basic syntax of SQL. Material will focus mainly on how to query databases. A web-based tool will be used for the tutorial.
URL:https://micde.umich.edu/event/intro-to-sql-6/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200420T140000
DTEND;TZID=America/Detroit:20200420T163000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000359-1587391200-1587400200@micde.umich.edu
SUMMARY:Geostatistical Analysis with R
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nGeostatistical approach models spatially correlated continuous random phenomenon for robust estimation and prediction. The approach is common across different fields in applied science where continuous phenomenon is observed at a few locations in space and the task is to estimate it at un-sampled locations. \nWe will use R to explore and develop an understanding of variogram and kriging and how they can be used for robust and unbiased interpolation of data over space. \nThis workshop will be offered remotely via BlueJeans.
URL:https://micde.umich.edu/event/geostatistical-analysis-with-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200417T090000
DTEND;TZID=America/Detroit:20200417T170000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000361-1587114000-1587142800@micde.umich.edu
SUMMARY:Introduction to Survey Design: Data Collection\, Questionnaire Design and Response Processes-Lecture
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nThis lecture-format workshop will present an overview of available modes and methods of survey data collection as well as an introduction to the survey response process and implications for questionnaire design. Participants will gain an appreciation of the tradeoffs inherent in survey design decisions and how design can affect data quality and survey errors. Topics will include: \nSurvey errors\, in particular measurement\, coverage\, and nonresponse error.\nWhat to consider when selecting a data collection method for a particular research question.\nMeasurement (response) error and how to reduce it through question wording/format and questionnaire structure.\nThe role of the interviewer and interviewee effects.
URL:https://micde.umich.edu/event/introduction-to-survey-design-data-collection-questionnaire-design-and-response-processes-lecture-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200413T150000
DTEND;TZID=America/Detroit:20200413T170000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000341-1586790000-1586797200@micde.umich.edu
SUMMARY:Statistical analysis with missing data in Python
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nMissing data arise in many fields of research\, and a large body of statistical tools has been developed to facilitate statistical analysis in the presence of missing data.  Here we focus mainly on multiple imputation\, which is a broadly-applicable approach for working with missing data. We will illustrate through several case studies how multiple imputation allows certain types of missing data to be rigorously accounted for\, while preserving the flexibility to use a variety of familiar statistical tools to account for other aspects of the data.   The analyses presented in this workshop will be performed in Python using the Statsmodels package. All software tools covered in this workshop are free and open source.
URL:https://micde.umich.edu/event/statistical-analysis-with-missing-data-in-python-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200406T150000
DTEND;TZID=America/Detroit:20200406T170000
DTSTAMP:20260604T013120
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000340-1586185200-1586192400@micde.umich.edu
SUMMARY:Mediation analysis in Python
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nMediation analysis is a set of tools for exploring hypotheses about causal pathways\, with a special focus on differentiating “direct” from “mediated” associations between an exposure and an outcome.  Many approaches to mediation analysis are based on regression analysis. In this workshop\, we will cover some of the basic ideas behind regression-based mediation analysis\, and show how this type of analysis can be performed in Python using the Statsmodels package.  All software tools covered in this workshop are free and open source.
URL:https://micde.umich.edu/event/mediation-analysis-in-python-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200402T140000
DTEND;TZID=America/Detroit:20200402T170000
DTSTAMP:20260604T013120
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000353-1585836000-1585846800@micde.umich.edu
SUMMARY:GIS analysis in R
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nR is a popular open source programming environment for statistics and data science. However\, it has also gradually become very powerful for GIS and spatial data science. \nThis workshop will help you learn about the tools and techniques available in R\, primarily for vector data analysis. Participants should register with the Census and get a census API key (https://api.census.gov/data/key_signup.html).
URL:https://micde.umich.edu/event/gis-analysis-in-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200325T100000
DTEND;TZID=America/Detroit:20200325T120000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000344-1585130400-1585137600@micde.umich.edu
SUMMARY:Building software projects: CMake is more than a build tool
DESCRIPTION:This workshop is a continuation of the previous workshop “Building software projects: use CMake to build the building plan”.  In this workshop\, we will see that CMake is not just a fancy Makefile generator: it can help us to test\, reuse\, and distribute our software!  We will use CMake to build two interdependent multi-language projects\, and demonstrate how to invoke unit tests after the build\, how to make our code discoverable and reusable by other software developers\, and how to create a distributable package.  If you intend to distribute your software to other research groups\, or if you expect that your project will grow beyond a few files of code and a few months of use — this workshop is for you! \nParticipants will need to have laptops with WiFi connection if they wish to follow the hands-on exercises.  A basic knowledge of Unix-like operating systems would be helpful in following and understanding the material\, but is not required.
URL:https://micde.umich.edu/event/building-software-projects-cmake-is-more-than-a-build-tool/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200324T100000
DTEND;TZID=America/Detroit:20200324T120000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000317-1585044000-1585051200@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/3601/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200323T150000
DTEND;TZID=America/Detroit:20200323T170000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000339-1584975600-1584982800@micde.umich.edu
SUMMARY:Go for data processing Part 2
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/go-for-data-processing-part-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200319T140000
DTEND;TZID=America/Detroit:20200319T160000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000324-1584626400-1584633600@micde.umich.edu
SUMMARY:Machine Learning in R
DESCRIPTION:In this workshop\, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training\, validation\, and testing sets; and cross-validation patterns for tuning hyper-parameters. Next\, we’ll apply these concepts to train models for identifying isolated letters from speech (https://archive.ics.uci.edu/ml/datasets/isolet). \nSpecifically\, we’ll apply the elastic net (a generalization of ridge and lasso regression)\, random forests\, and gradient boosting to this task.  We’ll briefly discuss each model/method but our primary focus will be on understanding the core functionality of the related R packages (glmnet\, randomForests\, xgboost) and tuning associated hyper-parameters.
URL:https://micde.umich.edu/event/machine-learning-in-r/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200316T150000
DTEND;TZID=America/Detroit:20200316T170000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000338-1584370800-1584378000@micde.umich.edu
SUMMARY:Go for data processing Part 1
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/go-for-data-processing-part-1/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200313T140000
DTEND;TZID=America/Detroit:20200313T163000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000349-1584108000-1584117000@micde.umich.edu
SUMMARY:Regular Expressions
DESCRIPTION:Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers\, passwords\, etc. in data entry. Regular expression capabilities can be found in a variety of programming languages and software like ArcGIS\, Java\, Javascript\, Matlab\, Perl\, PHP\, Python\, R\, Visual Basic\, etc. and some text editors. \nThe workshop will consist of hands-on example problems. Learn to search beyond “*.txt”. The tutorials will be conducted using Python. A basic programming background is helpful but not required for this workshop.
URL:https://micde.umich.edu/event/regular-expressions-4/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200310T083000
DTEND;TZID=America/Detroit:20200310T153000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000328-1583829000-1583854200@micde.umich.edu
SUMMARY:Introduction to SAS: Simple Inference Procedures
DESCRIPTION:Prerequisites: Participant should have some familiarity with introductory statistics and be able to load data into and perform basic data manipulations in SAS. \nIn this one-day\, six-hour workshop we will discuss the basics of using SAS for statistical inference and modeling. The workshop is held in a computer lab and will alternate between instructor presentations and attendee work sessions.  After this course the attendee will be able to perform\, in SAS\, basic statistical inference procedures (hypothesis tests\, confidence intervals) for a variety of data scenarios such as one-sample\, independent-samples\, and paired-sample t-tests; chi-square test of independence of two categorical variables;  correlation between two interval variables; ANOVA; simple and multiple linear regression; and simple and multiple logistic regression. Good statistical practice will be demonstrated but this workshop is not designed to teach statistics.
URL:https://micde.umich.edu/event/introduction-to-sas-simple-inference-procedures/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200309T150000
DTEND;TZID=America/Detroit:20200309T170000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000337-1583766000-1583773200@micde.umich.edu
SUMMARY:Survival analysis in Python
DESCRIPTION:Survival analysis is used when working with data that may be censored\, as often is the case in studies of human subjects with incomplete follow-up.  The presence of censoring makes most forms of regression and other standard statistical analyses inappropriate. A body of specialized techniques for analyzing this type of data has been developed\, including methods for estimating and comparing marginal survival functions\, and regression methods including the widely-utilized Cox proportional hazards model.  This workshop will briefly review the key principles of survival analysis\, then illustrate by example how various survival analysis methods can be carried out using Python with the Statsmodels package.  \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/survival-analysis-in-python-3/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200306T143000
DTEND;TZID=America/Detroit:20200306T160000
DTSTAMP:20260604T013120
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000323-1583505000-1583510400@micde.umich.edu
SUMMARY:R by Example: Functional Programming with data.table
DESCRIPTION:In the R by Example series of workshops\, we’ll discuss example analyses in R as a vehicle for learning  commonly used tools and programming patterns. The “Functional Programming with dplyr” workshop will initially focus on analyzing winter home temperatures in the US using data from the Residential Energy Consumption Survey (https://www.eia.gov/consumption/residential/).  We’ll use the data.table package for data manipulation\, and then demonstrate how to encapsulate the basic pattern within a function. Such functional programming allows us to repeatedly apply this pattern to answer other questions about this data. By using a function\, we make our code more concise and easier to understand. This workshop is geared towards intermediate to advanced R users\, or as a follow-up to the “Analyzing RECS using data.table” workshop.
URL:https://micde.umich.edu/event/r-by-example-functional-programming-with-data-table/
CATEGORIES:Workshops
END:VEVENT
END:VCALENDAR