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Training and Learning

Northwestern IT Research Computing Services collaborates with campus partners to offer members of the Northwestern research community opportunities to develop data science and computing skills, as well as learn about the services and resources that support research activities on campus.

Workshop topics include: R, Python, data visualization, SQL, Bash, high-performance computing (HPC), and more.  Northwestern Libraries offers workshops on GIS. See the Online Training tab for links to additional free training resources available for Northwestern researchers.

Subscribe to the NUIT-RESEARCH listserv to receive notice of research and training opportunities happening on and off campus.

Current Events

Workshops are currently offered online.  Additional online learning resources are also available for independent learning.


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R: dplyr

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R: dplyr

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R: dplyr


Beginning Quest: Quest Next Steps

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R: dplyr

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Data Exploration Using Glue

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R: tidyr

January
18-21
2022

R: Manipulating Data with dplyr

Tuesday-Friday, January 18-21 | 12-1pm | Online

Learn how to explore and manipulate data in R with the dplyr package, which is part of the tidyverse set of packages. In this four-part series, we'll cover the core dplyr functions for working with one data frame and joining multiple data frames together.

We'll also cover piping multiple commands together and how tibbles are different from regular data frames. Recordings of the workshops will be available only to those who register. The workshop materials are available at https://github.com/nuitrcs/r-tidyverse

  • Jan 18, 12-1pm: Tidyverse Basics
  • Jan 19, 12-1pm: dplyr: select, filter, mutate
  • Jan 20, 12-1pm: dplyr: group and summarize
  • Jan 21, 12-1pm: dplyr: joining data sets

Register 

January
20
2022

Beginning Quest: Quest Next Step

Thursday, January 20 | 1-2:30pm | Online

This 90-minute workshop builds on the introductory materials presented in our Introduction To Quest video. During this workshop you’ll be guided through a hands-on experience on Quest, Northwestern’s High Performance Computing cluster. You will use Quest to solve exercises, review how to submit jobs and troubleshoot them.

Prerequisites: Before attending this workshop, researchers new to Quest should:

Apply for a Quest allocation. We recommend “Research Allocation I” if you are new to Quest.

• Watch the Introduction to Quest video to get an overview of the system, learn how to submit jobs, and become familiar with best practices. To learn more about Quest, see About Quest.

• Become familiar with Unix command line: see our Intro Command Line and Bash Scripting workshops and check Online Resource Guide for learning basic command line skills.

Register 

January
27
2022

Data Exploration Using Glue

Thursday, January 27 | 3-4pm | Online

Data exploration is an important initial step in any research project, where you might examine your data by creating many plots, select different regions in parameter space to investigate, and explore how different datasets relate to one another. The Glue visualization application is an easy, but powerful, way to explore a variety of data types across multiple disciplines without any coding. In this workshop, I will provide an introduction to the basic functions of Glue through hands-on exercises.

Prior to the workshop please install Glue on your own computer; instructions can be found on this workshop's GitHub repository. I will provide a handful of datasets, though I also encourage you to bring your own data to explore with Glue. There are no other prerequisites for this workshop.

This workshop will be recorded; the link to view the recording will only be shared with those who are registered on Eventbrite. Please note that workshop registration closes two hours before the workshop begins.

Prerequisites: None.

Register 

January
31
2022

R: Pivoting and Separating with tidyr

Monday, January 31 | 12-1pm | Online

Learn how to change the shape of your data frame in R with the tidyr package from the tidyverse. This is one of the most common questions we get about R! We'll cover how to convert between long (many rows) and wide (many columns) data format and separate multiple pieces of information into separate columns or rows.

A recording of the workshop will be available only to those who register. The workshop materials are available at https://github.com/nuitrcs/r-tidyverse.

Prerequisition:This workshop assumes you are familiar with the dplyr package and the pipe operator.

Register 

Mon Tue Wed Thu Fri
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Quest: Scheduler, Job Arrays & Dependencies

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Next Steps in Python: Pandas

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Next Steps in Python: Pandas

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Next Steps in Python: Pandas

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Next Steps in Python: Pandas

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Next Steps in Python: Pandas

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February
3
2022

Quest: Scheduler, Job Arrays & Dependencies

Thursday, February 3 | 1-2:30pm | Online

This 90-minute remote workshop demonstrates how to optimize Quest job submissions for shorter wait times and faster run times, as well as scheduler techniques to submit many jobs at once.

In this workshop we'll leverage scheduler capabilities such as job arrays, job dependencies, and reporting.

Prerequisites: Familiarity with Quest will help you get the most out of this workshop, and our Introduction To Quest video is recommended.

Register 

February
21-25
2022

Next Steps in Python: Pandas

Monday, February 21 through Friday, February 25   | 3:30-4:30pm | Online

Pandas is a popular (and dense) Python module for working with DataFrames (data shaped in rows and columns, like csv and excel files). This 5-day workshop will cover the basics of Pandas to get you started working with your own data. We will cover:

  • why Pandas is useful
  • reading and writing files
  • selecting subsamples of data
  • grouping data
  • calculating summary statistics
  • making simple plots

Recordings will be provided each evening for anyone who is registered. You must be registered to receive the recording links.

Prerequisites: Participants should be familiar with basic Python at the level of the Python Fundamentals Bootcamp.

Register 

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Next Steps in Python: Scripts

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k-means Clustering with R

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March
1
2022

Next Steps in Python: Scripts

Tuesday, March 1 | 3:30-5pm | Online

This lesson is designed for beginning Python coders who have only been coding in Jupyter notebooks. Python scripts allow you to run Python code from the command line on your computer or on a server or cluster like Quest. Using Python scripts is a skill that will allow you to create computational pipelines and automate common tasks. It will generally make your code more modular, reusable, and reproducible. Scripts are also necessary for anyone who wants to create their own Python package.

A recording will be provided to anyone who is registered. You must be registered to receive the recording link.

Prerequisites: Participants should be familiar with basic Python at the level of the Python Fundamentals Bootcamp.

Register 

March
15
2022

k-means Clustering with R

Tuesday, March 15 | 11-12pm | Online

Appropriate for users familiar with R, this remote workshop will explore unsupervised machine learning with k-means clustering. Cluster analysis finds the natural groupings of data based on one or more measurements. As an unsupervised machine learning method, these algorithms have no dependent variable. The workshop will focus on k-means clustering and how to choose the optimal number of clusters.

Prerequisites: Familiarity with R.

Register 

Dataquest Online Courses

Access to Dataquest is available for researchers interested in learning or improving their skills with R, Python, SQL, and git through interactive, self-paced courses. Space is limited, and access is granted quarterly.

For more information and a link to the registration page, see Dataquest Access.

Research Computing Services Online Guides

Check out our curated lists of free, online books, exercises, tutorials, videos, and other resources for data science and programming skills.

O'Reilly/Safari Books Online

Northwestern University Libraries provides access to O'Reilly/Safari Books Online. This includes many popular books on programming, software development, and other technology topics. It also includes online tutorials. Students, faculty, and staff can register for an account with a Northwestern email address; access the link from the Northwestern network or VPN.

LinkedIn Learning

Northwestern offers access to LinkedIn Learning (formerly lynda.com) courses for students, faculty, and staff. Courses cover a wide range of technology and business topics including databases, programming, and data analysis.

For more information, see the Human Resources LinkedIn Learning page.

Previous Workshops

A selection of previous workshops is below. We offer many of these workshops at least once a year. If there is a particular workshop topic you're interested in, contact us to discuss options for hosting a workshop.  

Python

Introduction to Python
Next Steps in Python
Data Visualization with matplotlib
Pandas
Scikit-learn
Text Analysis with NLTK
Biopython
GeoPandas
Deep Learning with Tensorflow

R

Introduction to R
Tidyverse
Data Visualization with ggplot2
Shiny
Webscraping with rvest
Statistical Methods
Predictive Modeling
Social Network Analysis and Visualization
Text Analysis

Computing on Quest

Introduction to Quest
Introduction to Command Line
Bash Scripting
OpenMP
Singularity

Other Topics

Programming Concepts
Introduction to SQL
Designing and Creating Databases
Introduction to Git and GitHub
Intermediate Git and GitHub
Data Analysis with Tableau
Introduction to Data Visualization
MATLAB
Data Organization in Spreadsheets
Cloud Computing Essentials

Last Updated: 4 January 2022

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