Workshops and Learning Paths

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TDAI Data Literacy

As part of its Data Literacy program, TDAI periodically holds workshops aimed to introduce data and data analytics skills to the community.  These past workshops have included an R Crash Course and a series of introductory R workshops which include learning and using R and R Studio, statistical analysis in R, and visualizing data in R.

Furthering our Data Literacy mission, TDAI is pleased to be in partnership with the OSU Libraries to bring the Carpentries to the University.

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TDAI Workshop List - 2020-2021

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The Translational Data Analytics Institute regularly presents a multi-part workshop for learning R.  R is a free and open-source programming language used by many for statistical computing.  This series of workshops covers how to get started in R, use R in statistical analysis, and create visualizations in R.

Participants should have a computer (PC or Mac) and be able to sign up for a free account at the Ohio Supercomputer Center (OSC).  The Zoom meeting link and a link for accessing the project at OSC will be provided to participants.

For Spring 2021, all workshop sessions will be held via Zoom.  Meeting link will be provided to registered participants.

Getting Started in R – 2 sessions

3/19/2021, 9:30 – 11:30am
3/26/2021, 9:30 – 11:30am

Learn how to get started in R and Rstudio.  This workshop covers basic R functionality:  objects, functions, vectors, and various data operations.  Registering for this workshop signs you up for BOTH sessions, as the sessions build upon each other.  Sign up here.

Statistical Analysis in R – 1 session

4/2/2021, 9:30 – 11:30am

This workshop builds upon the Getting Started in R workshop and gives participants a foundation for performing statistical analysis using R.  Participants should already have completed the Getting Started in R workshop or have a working knowledge of using functions, vectors and data frames in R.  Sign up here

Data Visualization in R – 1 session

4/9/2021, 9:30 – 11:30am

This workshop builds upon the Getting Started in R workshop and gives participants a foundational understanding of what makes good visualizations and how to create them in R.  Participants should already have completed the Getting Started in R workshop or have a working knowledge of using functions, vectors, and data frames in R.  Sign up here

This workshop is held in partnership with the OSU Libraries Research Commons.

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This series of workshops in October is in celebration of Data Analytics Month at Ohio State

 

Getting Started in R – 2 sessions

Session 1 - October 5, 2020, 1-3pm
Session 2 - October 12, 2020, 1-3pm

In this workshop, you will learn how to get started in R and Rstudio.  This workshop covers basic R functionality:  objects, functions, vectors, and various data operations.  Registering for this workshop signs you up for BOTH Getting Started sessions, as the sessions build upon each other.

Statistical Analysis in R

Date and Time: October 19, 2020 from 1-3 pm

This workshop builds upon the Getting Started in R workshop and gives participants a foundation for performing statistical analysis using functions built into R.  Participants should already have completed the Getting Started in R workshop or have a working knowledge of objects, functions, vectors, and data operations in R.

Data Visualization in R

Date/Time: Oct 26, 1-3 pm

This workshop builds upon the Getting Started in R workshop and gives participants a foundational understanding of what makes good visualizations and how to create them in R.  Participants should already have completed the Getting Started in R workshop or have a working knowledge of using functions, vectors and data frames in R.

This workshop is held in partnership with the OSU Libraries Research Commons

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Workshop Calendar

See the calendar link below for TDAI workshop events, as well as Data related events hosted by TDAI partners at the OSU Libraries, the Ohio Supercomputer Center (OSC), and the Big Data and Analytics Association (BDAA).

Can’t find an event or workshop that meets your needs?  Look at the independent learning paths below for online tutorials and courses.

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Suggested Independent Learning Paths

Below are some suggested learning pathways designed to introduce you to data analytics or how to effectively use data.  Pick and choose from several pathways to customize your own learning experience to suit your needs and interests using a combination of both on-campus workshops and resources available on-line from LinkedIn Learning or Lynda.com.

For more information on obtaining accounts on either LinkedIn Learning through Ohio State, please see the criteria for access at the IT Academy’s eligibility page.  Public libraries (such as the Columbus Public Library) also provide access to these resources.

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Learning Paths

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This learning path may be useful for researchers and students that are starting to use the Ohio Supercomputer Center (OSC) resources for their research.  These events may be found in the calendar to the right, or on the OSC events page.

  1. Intro to Supercomputing at OSC
  2. Getting started at OSC
  3. Big Data at OSC Workshop
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This learning track uses material from lynda.com as an introduction to Data Analytics.  It may be supplemented with material available in workshops on campus as noted.

  1. Learning Data Analytics
  2. Data Science Foundations: Fundamentals
  3. Learning Data Science: Tell Stories with Data
  4. Data Science Foundations: Data Mining
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This learning path goes in depth on using Data to create an effective narrative.  It uses material from lynda.com as a baseline, and is supplemented with resources and workshops available from Research Commons.

  1. Data Visualization: Storytelling (1h 37m)
  2. Learning Data Visualization (3h 50m)
  3. Data Visualization Tips & Tricks (2h 14m)
  4. Research Commons Data Visualization tools series (pick one)

General Visualization

  1. Intro to Tableau for Data Visualization
  2. Intro to Excel for Data Visualization
  3. Open and Affordable tools for analyzing and visualizing data

GIS (mapping)

  1. Web mapping basics with ArcGIS online
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This learning track may be of interest to those wanting to use Amazon Web Services for their Data Analytics projects.  If the Big Data Technology Fundamentals is omitted it also makes a good introduction to AWS and cloud computing.

  1. AWS Cloud Practitioner Examples
  2. Introduction to Amazon EC2
  3. Amazon Simple Storage Service (S3) primer
  4. Big Data Technology Fundamentals
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Microsoft Developer has a series of videos on YouTube called “Python for Beginners”.  Each video is just a few minutes long and the series aims to help the viewer learn Python starting with very little programming background.