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DTSTART;TZID=America/Detroit:20190821T130000
DTEND;TZID=America/Detroit:20190821T160000
DTSTAMP:20230905T171403Z
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
UID:10000257-1566392400-1566403200@micde.umich.edu
SUMMARY:Introduction to the Great Lakes cluster and batch computing with Slurm
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 High Performance Computing Consultant in the Research Computing Services group of LSA TS 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\n\nLecture notes\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. \n\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: https://arc-ts.umich.edu/fluxform/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \n\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. \n\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 do not need to bring your own laptop to class. The classroom contains Windows or Mac computers\, which require your uniqname and UMICH (AKA Level 1) password to login\, and that have all necessary software pre-loaded. \nIf you want to use a laptop for the course\, you are welcome to do so:  please see our web page on Preparing your laptop to use Flux. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We cannot stop to debug connection issues with personal or departmental laptops during the class. \nIf you are unable to attend the presentation in person we will be offering a link into the live course via BlueJeans. Please register as if attending in person.  This will put you on the wait list but we will get your account setup for remote attendance.
URL:https://micde.umich.edu/event/introduction-to-the-great-lakes-cluster-and-batch-computing-with-slurm-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190725T130000
DTEND;TZID=America/Detroit:20190725T143000
DTSTAMP:20230905T171402Z
CREATED:20230905T171402Z
LAST-MODIFIED:20230905T171402Z
UID:10000240-1564059600-1564065000@micde.umich.edu
SUMMARY:Spin Class: No Sweat Reports in R
DESCRIPTION:If you use R\, there’s a decent chance you are already familiar with using Rmarkdown files and the knitr package to create reports documenting your analyses. A lesser known but equally useful function distributed with the knitr package is spin\, which gives you the power of Rmarkdown directly from an R script. This is especially powerful when creating quick\, memorandum-style documents which may be heavy on analysis but light on text. The power of spin lies in making it easy to interleave code\, output\, and text including all the bells and whistles of Rmarkdown but without the extra work of writing a separate Rmd file. \nIn this workshop\, I’ll discuss the basics of spin and its relationship to Rmarkdown and then provide participants with hands-on experience spinning up elegant\, reproducible\, analytic reports.
URL:https://micde.umich.edu/event/spin-class-no-sweat-reports-in-r/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190719T150000
DTEND;TZID=America/Detroit:20190719T163000
DTSTAMP:20230905T171402Z
CREATED:20230905T171402Z
LAST-MODIFIED:20230905T171402Z
UID:10000236-1563548400-1563553800@micde.umich.edu
SUMMARY:More Mixed Models
DESCRIPTION:In the R world\, lme4 is a great package for mixed model estimation\, and the most widely used for such models.  For standard settings\, few tools will do the trick as easily or as quickly\, and because of that\, its approach has been emulated in other packages and statistical programs.  However\, that ease and efficiency comes at a price of being able to do more complex models\, so at some point you may need to switch gears.  This workshop will demonstrate other ways to potentially get what you need. \nDemonstration will (potentially) include the following\, along with some discussion of strengths and/or drawbacks to use. \nglmmTMB: heterogenous variances\, autocorrelated residuals\, zero-inflated models\nrstanarm\, brms: bayesian approaches\nmgcv: additive effects\, robust models\, big data\nstatsmodels: in case you’re in the Python world. \nThis workshop assumes basic familiarity with mixed models\, and familiarity with R\, especially the lme4 package.  However\, this is a brief demonstration with a simple goal of bringing about awareness of other useful tools\, so one can simply attend to hear about them.
URL:https://micde.umich.edu/event/more-mixed-models/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190621T093000
DTEND;TZID=America/Detroit:20190621T160000
DTSTAMP:20230905T171402Z
CREATED:20230905T171402Z
LAST-MODIFIED:20230905T171402Z
UID:10000078-1561109400-1561132800@micde.umich.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Topics: \n\nBy the end of the workshop\, participants will be able to:\n\nWork with Stata\, including using Do-files and using the help system.\nGet data into Stata and manage your data files\nEstablish familiarity with your data\nClean the data to prepare it for analysis\nCheck for basic errors in the data\nGenerate new variables or manipulate existing variables\nMerge or reshape the data.\nProduce summary tables and descriptive statistics.\n\n\nNote: This is a full day workshop. To get the most out of it\, please plan to stay for the entire class.\n\n(Topics subject to change) \nIf you have questions about this workshop\, please send an email to jerrick@umich.edu
URL:https://micde.umich.edu/event/introduction-to-stata-3-3-2-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190620T150000
DTEND;TZID=America/Detroit:20190620T163000
DTSTAMP:20230905T171401Z
CREATED:20230905T171401Z
LAST-MODIFIED:20230905T171401Z
UID:10000235-1561042800-1561048200@micde.umich.edu
SUMMARY:R package demo: gganimate and patchwork
DESCRIPTION:This brief workshop will demonstrate the capabilities of two recent R packages\, gganimate and patchwork. One package allows the data explorer to provide some lively enhancement to an otherwise static plot\, without doing much more than standard plots with ggplot2. Likewise\, the other package can seamlessly combine multiple ggplots of varying kinds into one cohesive visualization. \nPrior knowledge of ggplot2 is required\, but not much else. Note also that this is just a demo. No statistical or analytical concepts will be discussed\, and while participation is certainly welcomed\, one can simply watch the demonstration.
URL:https://micde.umich.edu/event/r-package-demo-gganimate-and-patchwork/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190607T130000
DTEND;TZID=America/Detroit:20190607T163000
DTSTAMP:20230905T171401Z
CREATED:20230905T171401Z
LAST-MODIFIED:20230905T171401Z
UID:10000234-1559912400-1559925000@micde.umich.edu
SUMMARY:Advanced batch computing with Slurm on the Great Lakes cluster
DESCRIPTION:OVERVIEW\n\n\nThis workshop will cover some more advanced topics in cluster 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; troubleshooting and analysis; a brief introduction to workflow scripting using bash; parallel processing in one or more of Python\, R\, and MATLAB; and parallel profiling of C and Fortran code using Allinea Performance Reports and Allinea MAP of one or more of MPI and OpenMP programs. \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 High Performance Computing Consultant in the Research Computing Services group of LSA TS 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 (TBD)\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 Great Lakes user account\, a Great Lakes job account (one is created for each workshop)\, and be enrolled in Duo. The user account allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The job account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use against the account. Duo is required to help authenticate you to the cluster. \nGREAT LAKES USER ACCOUNT\nIf you already have a Flux user account\, you don’t need to do anything to obtain a Great Lakes user account.  Otherwise\, go to the Flux user account application page at: https://arc-ts.umich.edu/fluxform/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nGREAT LAKES JOB ACCOUNT\nWe create a job 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 Great Lakes job account\, you can use that\, though if there are any issues with that job account\, we will ask you to use the workshop job 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 do not need to bring your own laptop to class. The classroom contains Windows or Mac computers\, which require your uniqname and UMICH (AKA Level 1) password to login\, and that have all necessary software pre-loaded. \nIf you want to use a laptop for the course\, you are welcome to do so:  please see our web page on Preparing your laptop to use Flux. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We cannot stop to debug connection issues with personal or departmental laptops during the class. \n\nIf you are unable to attend the presentation in person we will be offering a link into the live course via BlueJeans. Please register as if attending in person.  This will put you on the wait list but we will get your account setup for remote attendance.
URL:https://micde.umich.edu/event/advanced-batch-computing-with-slurm-on-the-great-lakes-cluster/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190531T130000
DTEND;TZID=America/Detroit:20190531T163000
DTSTAMP:20230905T171401Z
CREATED:20230905T171401Z
LAST-MODIFIED:20230905T171401Z
UID:10000233-1559307600-1559320200@micde.umich.edu
SUMMARY:Introduction to the Great Lakes cluster and batch computing with Slurm
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 High Performance Computing Consultant in the Research Computing Services group of LSA TS 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\n\nLecture notes (TBD)\nGreat Lakes Slurm HPC cluster\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a Great Lakes user account\, a Great Lakes job account (one is created for each workshop)\, and be enrolled in Duo. The user account allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The job account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use against the account. Duo is required to help authenticate you to the cluster. \n\nGREAT LAKES USER ACCOUNT\nIf you already have a Flux user account\, you don’t need to do anything to obtain a Great Lakes user account.  Otherwise\, go to the Flux user account application page at: https://arc-ts.umich.edu/fluxform/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \n\nGREAT LAKES JOB ACCOUNT\nWe create a job 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 Great Lakes job account\, you can use that\, though if there are any issues with that job account\, we will ask you to use the workshop job account. \n\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 do not need to bring your own laptop to class. The classroom contains Windows or Mac computers\, which require your uniqname and UMICH (AKA Level 1) password to login\, and that have all necessary software pre-loaded. \nIf you want to use a laptop for the course\, you are welcome to do so:  please see our web page on Preparing your laptop to use Flux. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We cannot stop to debug connection issues with personal or departmental laptops during the class. \nIf you are unable to attend the presentation in person we will be offering a link into the live course via BlueJeans. Please register as if attending in person.  This will put you on the wait list but we will get your account setup for remote attendance.
URL:https://micde.umich.edu/event/introduction-to-the-great-lakes-cluster-and-batch-computing-with-slurm/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190521T130000
DTEND;TZID=America/Detroit:20190521T170000
DTSTAMP:20260522T154048Z
CREATED:20230905T171400Z
LAST-MODIFIED:20260522T154048Z
UID:10000040-1558443600-1558458000@micde.umich.edu
SUMMARY:Introduction to the Flux cluster and batch computing
DESCRIPTION:Overview\nThis workshop will provide a brief overview of the components of the Flux 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. \nPrerequisites\nObtain a user account on Flux. If you do not have a Flux user account\, click here to go to the account application page at: https://arc-ts.umich.edu/fluxform/ \nRegister for Duo authentication. See below for details. \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. \nInstructor\nBennet Fauber\nScientific Applications Analyst\nAdvanced Research Computing — Technology Services \nBennet Fauber is a member of the technical team that administers the Flux cluster. \nMaterials\nIn-class handouts\n\nOutput from qstat\nOutput from checkjob\nOutput from mdiag\nOutput from showq\n\nSupplementary materials\n\nFlux in Ten Easy Steps\nUsing PBS\nUsing software modules\nLinking libraries with applications\nEstablishing and managing a Flux project allocation\n\n\nCourse Preparation\nIn order to participate successfully in the workshop exercises\, you must have a Flux user account and be registered for the Duo authentication service. The user account allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare Flux jobs for submission. Information about registering for Duo is at the ITS Two Factor Authentication web page. \nFlux user account\nA single Flux user account can be used to prepare and submit jobs using various allocations. If you already already possess a user account\, you can use it for this course\, you can skip to “Flux allocation” below. If not\, please visit https://arc-ts.umich.edu/fluxform to obtain one. A user account is free to members of the University community. Please note that obtaining an account requires human processing\, so be sure to do this at least two business days before class begins. \nFlux allocation\nWe create an allocation 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 allocation 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 Flux allocation\, you can use that\, though if there are any issues with that allocation\, we will ask you to use the workshop allocation. \nLaptop Preparation\nThe classroom contains Windows computers\, which require your uniqname and UMICH password to login\, and which have all necessary software preloaded. \nIf you want to use a laptop for the course\, you are welcome to do so. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We will try to help resolve issues after the workshop. \nIf you want to try to prepare your laptop for use in the class\, please see our web page on Preparing your laptop to use Flux. If you have a Windows computer\, we recommend that you install PuTTY/WinSCP from the Blue Disc web site. Macintosh computers typically have the minimum requirements installed as part of the system. \nMore help\nPlease use our class mailing list hpc101course@umich.edu for questions\, comments\, or to seek further assistance.
URL:https://micde.umich.edu/event/introduction-to-the-flux-cluster-and-batch-computing-5-2-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190520T130000
DTEND;TZID=America/Detroit:20190520T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000217-1558357200-1558368000@micde.umich.edu
SUMMARY:Advanced batch computing on the Flux cluster
DESCRIPTION:This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob\, qstat\, and other tools; and parallel debugging and profiling of C and Fortran code\, including logging\, gdb (line-oriented debugging)\, ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs. We will issue you a temporary allocation to use for the course\, or you can use your existing Flux allocations\, if any. \nCourse Prerequisites:  Introduction to Batch Computing on Flux or equivalent. This course assumes familiarity with the Linux command line\, text editing on Linux\, and a basic understanding of Flux including how to submit and track jobs. \nPlease use our class mailing list hpc101course@umich.edu for questions\, comments\, or to seek further assistance.
URL:https://micde.umich.edu/event/advanced-batch-computing-on-the-flux-cluster-8/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190515T130000
DTEND;TZID=America/Detroit:20190515T170000
DTSTAMP:20260522T154510Z
CREATED:20230905T171400Z
LAST-MODIFIED:20260522T154510Z
UID:10000006-1557925200-1557939600@micde.umich.edu
SUMMARY:Introduction to the Flux cluster and batch computing
DESCRIPTION:Overview\nThis workshop will provide a brief overview of the components of the Flux 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. \nPrerequisites\nObtain a user account on Flux. If you do not have a Flux user account\, click here to go to the account application page at: https://arc-ts.umich.edu/fluxform/ \nRegister for Duo authentication. See below for details. \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. \nInstructor\nBennet Fauber\nScientific Applications Analyst\nAdvanced Research Computing — Technology Services \nBennet Fauber is a member of the technical team that administers the Flux cluster. \nMaterials\nIn-class handouts\n\nOutput from qstat\nOutput from checkjob\nOutput from mdiag\nOutput from showq\n\nSupplementary materials\n\nFlux in Ten Easy Steps\nUsing PBS\nUsing software modules\nLinking libraries with applications\nEstablishing and managing a Flux project allocation\n\n\nCourse Preparation\nIn order to participate successfully in the workshop exercises\, you must have a Flux user account and be registered for the Duo authentication service. The user account allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare Flux jobs for submission. Information about registering for Duo is at the ITS Two Factor Authentication web page. \nFlux user account\nA single Flux user account can be used to prepare and submit jobs using various allocations. If you already already possess a user account\, you can use it for this course\, you can skip to “Flux allocation” below. If not\, please visit https://arc-ts.umich.edu/fluxform to obtain one. A user account is free to members of the University community. Please note that obtaining an account requires human processing\, so be sure to do this at least two business days before class begins. \nFlux allocation\nWe create an allocation 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 allocation 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 Flux allocation\, you can use that\, though if there are any issues with that allocation\, we will ask you to use the workshop allocation. \nLaptop Preparation\nThe classroom contains Windows computers\, which require your uniqname and UMICH password to login\, and which have all necessary software preloaded. \nIf you want to use a laptop for the course\, you are welcome to do so. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We will try to help resolve issues after the workshop. \nIf you want to try to prepare your laptop for use in the class\, please see our web page on Preparing your laptop to use Flux. If you have a Windows computer\, we recommend that you install PuTTY/WinSCP from the Blue Disc web site. Macintosh computers typically have the minimum requirements installed as part of the system. \nMore help\nPlease use our class mailing list hpc101course@umich.edu for questions\, comments\, or to seek further assistance.
URL:https://micde.umich.edu/event/introduction-to-the-flux-cluster-and-batch-computing-5-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190513T090000
DTEND;TZID=America/Detroit:20190513T120000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000210-1557738000-1557748800@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\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS 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 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-7-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190510T130000
DTEND;TZID=America/Detroit:20190510T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000209-1557493200-1557504000@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\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS 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 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-7-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190425T130000
DTEND;TZID=America/Detroit:20190425T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000223-1556197200-1556208000@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Data Science,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190417T130000
DTEND;TZID=America/Detroit:20190417T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000222-1555506000-1555516800@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Data Science,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190416T093000
DTEND;TZID=America/Detroit:20190416T120000
DTSTAMP:20230905T171359Z
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000101-1555407000-1555416000@micde.umich.edu
SUMMARY:Web Scraping with Python
DESCRIPTION:This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests\, beautifulsoup\, retry modules and the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.
URL:https://micde.umich.edu/event/web-scraping-with-python-3-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190403T130000
DTEND;TZID=America/Detroit:20190403T160000
DTSTAMP:20230905T171359Z
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000218-1554296400-1554307200@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190322T093000
DTEND;TZID=America/Detroit:20190322T160000
DTSTAMP:20230905T171358Z
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000077-1553247000-1553270400@micde.umich.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Topics: \n\nBy the end of the workshop\, participants will be able to:\n\nWork with Stata\, including using Do-files and using the help system.\nGet data into Stata and manage your data files\nEstablish familiarity with your data\nClean the data to prepare it for analysis\nCheck for basic errors in the data\nGenerate new variables or manipulate existing variables\nMerge or reshape the data.\nProduce summary tables and descriptive statistics.\n\n\nNote: This is a full day workshop. To get the most out of it\, please plan to stay for the entire class.\n\n(Topics subject to change) \n 
URL:https://micde.umich.edu/event/introduction-to-stata-3-3-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190320T153000
DTEND;TZID=America/Detroit:20190320T170000
DTSTAMP:20230905T171358Z
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000219-1553095800-1553101200@micde.umich.edu
SUMMARY:Doing more with RStudio
DESCRIPTION:This talk will serve as an demonstration of what RStudio can offer for those that do not use it\, as well as a showcase for more advanced use for those who use it only for scripting purposes. \nTopics include but are not limited to: \n\nScripting shortcuts\nCustomization\nUsing Projects\nDocument generation\nAddins\nPackage Development\nDebugging and Profiling\nVersion Control\n\nWhile this is more of a demo than a workshop\, attendees are encouraged to try some things out and explore as we go along. \n If you have questions about this workshop\, please send an email to micl@umich.edu
URL:https://micde.umich.edu/event/doing-more-with-rstudio/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190319T100000
DTEND;TZID=America/Detroit:20190319T120000
DTSTAMP:20230905T171358Z
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000203-1552989600-1552996800@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. \nAll examples will use Python; some familiarity with Pyt hon is recommended. Computers will be available to complete exercises.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-3-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190315T093000
DTEND;TZID=America/Detroit:20190315T120000
DTSTAMP:20230905T171358Z
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000213-1552642200-1552651200@micde.umich.edu
SUMMARY:Intro to Web Applications using Flask and Python
DESCRIPTION:Ever want to build your own web application? Do you want to do it using Python? Well then\, Flask is the answer you are looking for. Its a micro web framework for Python to help you build your first web app. Come learn how to get started building\, testing and deploying your first app to the web. \nAttendees should be familiar with HTML\, CSS and Python or RShiny. Anaconda Python 3.6 will be used.
URL:https://micde.umich.edu/event/into-to-web-applications-using-flask-and-python/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190313T140000
DTEND;TZID=America/Detroit:20190313T163000
DTSTAMP:20230905T171359Z
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000212-1552485600-1552494600@micde.umich.edu
SUMMARY:PySpark
DESCRIPTION:Apache Spark is a powerful open source processing engine built around speed\, ease of use\, and sophisticated analytics. Industry has quickly adopted Spark and deployed it at scale for processing big data. Its main advantage include in-memory processing and a rich set of operations for wrangling data using DataFrames. In this workshop\, we’ll introduce attendees to SparkSQL and DataFrames for basic data manipulation\, file I/O and SQL querying. Spark has language bindings to R\, Python\, Scala and Java. We’ll be using PySpark (the Python API) in our workshop. \nThe workshop is intended for users with INTERMEDIATE knowledge of R\, Python\, or comparable language. Attendees should be familiar with DataFrames in Python (pandas) or R (dplyr). Attendees will NEED to have a Cavium account beforehand to participate. http://myumi.ch/6pn5d
URL:https://micde.umich.edu/event/pyspark/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190306T140000
DTEND;TZID=America/Detroit:20190306T170000
DTSTAMP:20260401T195302Z
CREATED:20230905T171359Z
LAST-MODIFIED:20260401T195302Z
UID:10000187-1551880800-1551891600@micde.umich.edu
SUMMARY:Latent Variable Modeling
DESCRIPTION:Part of the Structural Equation Modeling (SEM) series.  This workshop will help participants develop skills in understanding and conducting latent variable models\, particularly from the perspective of structural equation modeling. After a conceptual overview\, a broad view of matrix factorization techniques will be provided along with specific examples (e.g. PCA\, ‘factor analysis’).  In addition\, measurement error issues\, reliability\, and scale development will be discussed (e.g. ‘confirmatory’ factor analysis). \nPrerequisites: One should have a firm understanding of basic regression. R will be the program of choice\, but nothing beyond very basic skill is assumed (e.g. import data\, run a regression).  Demonstration will be conducted with R\, and the psych and lavaan packages in particular.
URL:https://micde.umich.edu/event/latent-variable-modeling/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190305T083000
DTEND;TZID=America/Detroit:20190305T150000
DTSTAMP:20230905T171359Z
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000039-1551774600-1551798000@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (March 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r-2-2-2-2/2019-03-05/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190304T083000
DTEND;TZID=America/Detroit:20190304T150000
DTSTAMP:20230905T171359Z
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000038-1551688200-1551711600@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (March 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190226T100000
DTEND;TZID=America/Detroit:20190226T120000
DTSTAMP:20230905T171357Z
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000202-1551175200-1551182400@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. \nAll examples will use Python; some familiarity with Pyt hon is recommended. Computers will be available to complete exercises.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190220T153000
DTEND;TZID=America/Detroit:20190220T173000
DTSTAMP:20230905T171358Z
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000185-1550676600-1550683800@micde.umich.edu
SUMMARY:Generalized Additive Models
DESCRIPTION:Nonlinear relationships abound in nature\, though typical statistical models ignore this in favor of simplicity\, often at a cost of both predictive capabilities and better understanding of the underlying phenomenon of interest.  One means to explore such relationships is through generalized additive models (GAM). \nThis workshop will introduce participants to GAMs as a means to extend their efforts beyond the usual GLM setting.  In addition\, extensions and connections to other models will be noted (e.g. mixed and spatial).  Demonstration will be conducted with R\, and the mgcv package in particular. \nLink: https://m-clark.github.io/generalized-additive-models/
URL:https://micde.umich.edu/event/generalized-additive-models-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190212T093000
DTEND;TZID=America/Detroit:20190212T120000
DTSTAMP:20230905T171345Z
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000204-1549963800-1549972800@micde.umich.edu
SUMMARY:Python for Data Analysis
DESCRIPTION:Learn data analysis with Python. We’ll be using pandas\, the go-to Python library used for data wrangling and analysis. We’ll be practicing with several different real-world datasets (e.g. time-series\, text) and learning how to read\, write\, clean\, transform\, merge and reshape data.  \nThe workshop is intended for users with basic Python knowledge. Anaconda Python 3.6 and a Jupyter Notebook will be used.
URL:https://micde.umich.edu/event/python-for-data-analysis-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190207T130000
DTEND;TZID=America/Detroit:20190207T170000
DTSTAMP:20230905T171357Z
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000183-1549544400-1549558800@micde.umich.edu
SUMMARY:Mixed Models with R
DESCRIPTION:Mixed models are an extremely useful modeling tool for situations in which there is some dependency among observations in the data\, where the correlation typically arises from the observations being clustered in some way. For example\, it is quite common to have data in which we have repeated measurements for the units of observation\, or in which the units of observation are otherwise clustered (e.g. students within school\, cities within geographic region). While there are different ways to approach such a situation\, mixed models are a very common and powerful tool to do so.  In addition\, they have ties to other statistical approaches that further expand their applicability. \nThe goal of this workshop is primarily to provide a sense of when one would use mixed models and how to incorporate a variety of standard techniques.  It is very applied in nature\, and only assumes a basic understanding of standard regression models (and use of R for such models). \nLink: https://m-clark.github.io/mixed-models-with-R/
URL:https://micde.umich.edu/event/mixed-models-with-r-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190206T110000
DTEND;TZID=America/Detroit:20190206T130000
DTSTAMP:20230905T171423Z
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000182-1549450800-1549458000@micde.umich.edu
SUMMARY:Introduction to Programming with Python & Matlab
DESCRIPTION:This is a four-part workshop introducing programming concepts to those with little-to-no programming experience. \nThe four 2-hour sessions will take place over two weeks\, with Python being taught in the first three sessions\, and Matlab in the fourth session. Computers are provided. \nSession 1: Feb 6\, 11am – 1pm – Location: MLB 2001a \nSession 2: Feb 7\, 11am – 1pm –  Location: MLB 2001A \nSession 3: Feb 13\, 11am – 1pm – Location: MLB 2001A \nSession 4: Feb 14\, 11am – 1pm – Location: MLB 2001A
URL:https://micde.umich.edu/event/introduction-to-programming-with-python-matlab/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190205T083000
DTEND;TZID=America/Detroit:20190205T150000
DTSTAMP:20230905T171424Z
CREATED:20230905T171424Z
LAST-MODIFIED:20230905T171424Z
UID:10000037-1549355400-1549378800@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (February 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r-2-2-2/2019-02-05/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
END:VCALENDAR