Research Guides

Courses and Workshops


Working with Data Online Workshops Registration Now Available

Click to access the workshop registration page for Fall 2020



 
Working with Data Online Workshops Registration Now Available
Downloadable "Flipped" Instructional Content
Data Services Online Workshops

Data Services at the University of Miami Libraries offers a "Working with Data" workshop series every semester. This series of seminars and workshops is designed for students, staff, and faculty who are undertaking research in any discipline.

Flipped Online Workshops
Due to the COVID-19 pandemic, we have switched to two approaches: online workshops and a flipped classroom approach. In order to participate in the flipped workshops, you are encouraged to follow these steps:
  1. Download the instructional material (tutorial and data) for each workshop. The download links are listed in the description for each workshop below.
  2. Go through the workshop material on your own time, writing down questions for the instructor. If you have trouble accessing the software necessary for the workshop, please contact criopelle@miami.edu for assistance. Many of the software programs are available at https://www.it.miami.edu/services-and-products/software/students/index.html.
  3. Book an online Zoom-based appointment with the instructor to discuss your questions and receive additional instruction (as necessary).
Online Digital Scholars' Lab
Due to the COVID-19 pandemic, we are offering our Digital Scholars’ Lab as an online service. To gain access to the online Digital Scholars’ Lab, go to Remote Labs and following the instructions to begin.
 
Dr. Cameron Riopelle Data Analysis Software Instruction
Presented by Dr. Cameron Riopelle, Head of Data Services

Gain introductory experience with data analysis in a variety of new software environments, particularly R, SPSS, SAS, and Tableau, paired with discussions of research methods and data science best practices.
  • Intro and Intermediate SPSS (download link)
  • Introduction and Intermediate R/RStudio (download link)
    • Please note: the .R files are the script for the workshops (containing the tutorials themselves) which must be opened from within R or RStudio.
  • R for Data Visualization (download link)
  • NVivo (download link)
  • SAS (download link)

Dr. Timothy Norris Research Data Management Series
Presented by Dr. Timothy Norris, Data Scientist

This workshop provides students with strategies to increase productivity (efficiency), enable proper data stewardship (security), and help students exceed data management expectations and requirements in the research environment (compliance).

Dr. Jorge Quintela GIS Software Instruction
Presented by Dr. Jorge Quintela, GIS and Data Specialist

This workshop will introduce you to GIS tools and techniques using ArcGIS Online. You will learn how to create interactive maps; how to add, manage, and share content; and how to perform basic spatial analysis procedures with your data. Please note: if you do not have the proper credentials for this software program, contact Dr. Quintela in advance for assistance. Additional training: short (2-page) instructional documents on GIS techniques using ArcGIS Pro. Please note: if you do not have the proper credentials for this software program, contact Dr. Quintela in advance for assistance.
  • Add (Calculate) Geometry Attributes in ArcGIS Pro (download link)
  • ArcGIS Pro Count the number of points inside polygons using Spatial Join (download link)
  • ArcGIS Pro: Join an excel or csv table to a feature layer (download link)
  • Determining  the predominant type of features when overlaying two polygon layers (download link)
  • Clipping a raster in ArcGIS Pro (download link)
  • Export an attribute table from ArcGIS Pro to Excel (download link)
  • Deriving a slope surface in ArcGIS Pro (download link)
  • Deriving an aspect surface in ArcGIS Pro (download link)
  • Editing the style of a vector tile in ArcGIS (download link)
  • Creating a profile graph from a surface in ArcGIS Pro (download link)

Kineret Ben-Knaan Introduction to Google Data Studio and Microsoft Power BI
Presented by Kineret Ben-Knaan, Research & Assessment Librarian

This workshop series will introduce participants to using different data visualization tools. Participants will learn how to connect to diverse datasets and create visual dashboards that can be shared with colleagues. Please contact criopelle@miami.edu to arrange this workshop over Zoom.

James Sobczak Introduction to Zotero and OpenRefine Series
Presented by James Sobczak, STEM Librarian

Gain introductory experience organizing information through the use of reference management software (Zotero) and data cleaning tools (OpenRefine). Please contact criopelle@miami.edu to arrange this workshop over Zoom.
 
Online Office Hours
The Data Services team holds online office hours for instruction and consultation for all patrons at all campuses at the University of Miami, including Coral Gables, medical, and RSMAS.

Stop by and introduce yourself and ask questions!

You can schedule an appointment for a consultation or instruction at the Data Services YouCanBook.Me page or through email (contacting the relevant staff member). Meetings will be conducted online over Zoom, with the meeting invitation sent out before the meeting.
Learn software for research
Full list of current software/languages supported by Data Services (alphabetical):
Fall 2020 RSMAS Online Data Workshops

Multiple Online Workshops Available

Fall 2020

 

Learn software programs for research and data analysis. This series of online Zoom seminars and workshops is offered to campus students, faculty, and staff who are undertaking research. It is not required to be a member of RSMAS campus activity to attend; however, this series is advertised primarily on RSMAS campus email lists to ensure availability to RSMAS campus students, faculty, staff, and researchers. In addition, people who cannot attend these workshops are encouraged to attend the additional workshops offered in the "Courses and Workshops" tab above.

Registration is through Zoom. Workshops will not be required; instead, detailed annotated tutorial files will be publicly released for at-home learning and placed on this site for future reference.


Registration is manually approved and capped at 40 participants. If you run into issues with registration, or have any questions, please email dataservices@miami.edu.

 
  • Introduction to R, October 12th 2-4pm (register)
    • Designed for new R and R Studio users. It provides an introduction to the R software program, including its programming language, software-environment, importing data, descriptive statistics, transforming variables, selecting and splitting data, exploratory tests, and visualization.
  • Intermediate R, October 13th 2-4pm (register)
    • Designed for intermediate R and R Studio users. It covers common statistical methods in R such as means comparisons, ANOVA, linear regression, and basic visualization.
  • R for Data Visualization, October 19th 2-4pm (register)
    • Introduction to using the software program R for visualization. Prior experience with R required--this workshop assumes knowledge of the R language and environment.
  • Introduction to Python for Data Analysis, October 20th 2-4pm (register)
    • This workshop is an introduction to the programming language Python using the Jupyter environment. The basics of using Python for data analytis are covered, including using Jupyter, importing data, using popular libraries such as pandas and NumPy, data visualization, and saving/exporting.
  • Introduction to Tableau for Data Visualization, October 26th 1-2:30pm (register)
    • Participants will learn the basics of data visualization using the software program Tableau, including connecting to data, visualizing univariate and bivariate data, visualization design, building dashboards, and online sharing.
SWC logo white

Teaching basic lab skills
for research computing


"Software Carpentry is global organization dedicated to teaching researchers the computing skills they need to get more done in less time and with less pain. Volunteer instructors have run hundreds of events for more than 34,000 researchers since 2012. All of the lesson materials are freely reusable under the Creative Commons - Attribution license" (https://software-carpentry.org/about/).

"A Software Carpentry workshop is taught by at least one trained and badged instructor. Over two days, instructors teach our three core topics: the Unix shell, version control with Git, and a programming language (Python or R)" (https://software-carpentry.org/lessons/).
 

Upcoming Fall 2020 Workshops:
  • Python for Scientific Computing : November 9-10 (virtual) - details forthcoming
 

Through generous support from the Institute for Data Science and Computing, the University of Miami Libraries and the University of Miami Graduate School, the University of Miami maintains a formal relationship with the Software Carpentry Organization. Benfits of this relationship include annual instructor training for UM graduate students, faculty and staff who would like to join the Software Carpentry volunteer teaching corps and the opportunity to host several Software Carpentry workshops each semester.

Please contact research data services if you are interested in software carpentry training or would like a workshop organized as a special event in your department or school.

Fall 2020:  Workshop Series - Working with Data

Gain introductory experience with data analysis in a variety of new software environments, particularly SPSS, R, and RedCap, paired with discussions of statistical analysis and data science best practices.

Instructors: Dr. Thilani Samarakoon, Biomedical Data Librarian and Dr. Cameron Riopelle, Head of Data Services
Contact: thilani.samarakoon@miami.edu

This workshop series is offered online via Zoom.
Click here to register for the workshops

Introduction to Tableau
Tableau is a data visualization software that allows to transform data into plots and tables. Here you will learn about the Tableau workspace consisting of menus, toolbars, and the data pane. In addition, the workshop covers topics on connecting to the data, building data visualizations and dashboards, and sharing them. Previous experience with Tableau is not necessary.

Tuesday, September 29, 2020 from 5:30-7 p.m.

 


 
Introduction to R
R is an open-source software environment for statistical computing and graphics. This workshop is designed to introduce R, RStudio and R Markdown. You will learn to install R packages and utilize their functionalities for exploratory data analysis(EDA). It covers basic data types, importing data, cleaning and plotting data, and analyzing relationships between variables. Previous experience with R is not necessary.

Thursday, October 1, 2020 from 5:30-7 p.m.
 
Data Visualization with R
Here we will focus on creating visualizations using R packages like ggplot2. This covers basic plots and best practices in data visualization. Some experience with R is preferred.

Tuesday, October 6, 2020 from 5:30-7 p.m.
 
Intermediate R
The workshop covers handling NA's, selecting variables for linear regression models, exploring linear and logistic regression and creating specific plots like survival curves and forest plots. Some experience with R is preferred.

Thursday, October 8, 2020 from 5:30-7 p.m.

 

Introduction to SPSS
Designed for new SPSS users. It provides an introduction to the SPSS software program, including its software environment, importing data, descriptive statistics, transforming variables, selecting and splitting data, and visualization.

Tuesday, October 13, 2020 from 5:30-7 p.m.

 

Intermediate SPSS
Designed for intermediate SPSS users. It covers common statistical methods in SPSS such as means comparisons, ANOVA, linear regression, and logistic regression models.

Thursday, October 15, 2020 from 5:30-7 p.m.

 

REDCap
REDCap (Research Electronic Data Capture) is a Web-based application that allows you to quickly build and manage databases and online surveys. This workshop will show you how to: build case report forms to enter data extracted from any source; automatically check for errors to guard against bad data; produce online summary statistics and graphics; make analyzable, anonymized datasets; export data to Excel and major statistical packages like R, SAS, SPSS, STATA, and other basic concepts.

Tuesday, October 20, 2020 from 5:30-7 p.m.


 

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