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Training and Events

Northwestern IT Research Computing Services collaborates with campus partners to offer members of the Northwestern research community opportunities to learn about the advanced research services and resources that support research activities on campus.

Remember to follow us on Twitter @NUITResearch and subscribe to the NUIT-RESEARCH listserv for information about research and training opportunities happening on and off campus.

Computational Skills for Researchers (CSR)

Research Computing Services offers workshops on programming, data analysis, and other technical skills for Northwestern researchers. All members of the Northwestern research community are welcome. There is no cost to attend, but registration is required.  Workshops are in Mudd Hall on the Evanston campus unless otherwise noted. See a list of available workshops.

DataCamp Online Courses for R and Python

Research Computing is providing access to DataCamp for students, faculty, and staff interested in learning or improving their skills with R and Python through interactive, self-paced courses. Space is limited. To apply for access to DataCamp over the summer, you must first complete one of DataCamp's free, introductory courses or request access to advanced courses.

For more information and a link to the registration page, see DataCamp for R and Python.

The Researcher's Toolkit

The Researcher's Toolkit is a workshop series designed to help Northwestern researchers improve scholarly productivity and efficiency in the areas of version control, publication resources, scientific computing, operating systems, geographic information systems (GIS), and software training.

See the list of fall workshop topics.

Computational Skills for Informatics

Galter Library, NUIT Research Computing and NUCATS are bringing back Computational Skills for Informatics ("CSI").

See the list of fall workshop topics.

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Select Past Events

Computational Research Day

The Fourth Annual Computational Research Day was held on April 18, 2017. This all-day, campus-wide event is designed to showcase computational research at Northwestern, as well as strengthen the computational research community at Northwestern. Highlights of the day included presentations from Northwestern researchers and guest speakers workshopsBirds of a Feather sessions, product and vendor demos, and a poster competition

Learn more

Intro to R

The in-person, six hour workshop is appropriate for those with some data analysis experience but limited or no experience with R. The workshop will cover the basics of reading and writing data files, manipulating data sets, data types and structures, plotting, and the RStudio environment.

Intro to Python

This two-day workshop teaches programming fundamentals using the Python language.  The workshop is appropriate for those with limited previous programming experience.  This workshop combines live-coding presentations and exercise sessions where participants practice their new Python skills with the help of instructors and assistants. 

Python for Data Analysis

This two-day workshop gives participants experience with Python packages for reading, manipulating, visualizating, and analyzing data.  We cover NumPy, pandas, matplotlib, Seaborn, statsmodels, and Scikit-learn.  Familiarity with basic Python programming and prior data analysis experience are prerequisites.  

Data Analysis, Visualization, and Automation with MATLAB

MATLAB is a high-level language and interactive environment for data analysis, visualization, and numerical computation. Using MATLAB, you can reach solutions faster and easier than with spreadsheets or other programming languages, such as C/C++, Java or Python.  In this session, we provide an overview of MATLAB and introduce the powerful statistical analysis and visualization capabilities available in the MATLAB product family. We demonstrate how to analyze and visualize data, introduce desktop tools for editing code, and show how to publish and share results.  This introductory seminar is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed.

Machine Learning with MATLAB

Engineers and data scientists work with large amounts of data in a variety of formats such as sensor, image, video, telemetry, databases, and more. They use machine learning to find patterns in data and to build models that predict future outcomes based on historical data.  In this session, we explore the fundamentals of machine learning using MATLAB. We introduce machine learning techniques available in MATLAB to quickly explore your data, evaluate machine learning algorithms, compare the results and apply the best technique to your problem.

Computational Skills for Informatics Seminar Series

The Computational Skills for Informatics (CSI) Seminar is a series of presentations and hands-on workshops for Northwestern researchers designed to offer insight on topics relevant to bioinformatics and large dataset management and computation. All sessions are held on the Chicago campus and are one to two hours in length, depending on the topic.  Space is limited and registration is required.

The CSI Seminar Series is hosted in collaboration with Galter Health Sciences Library, NUCATS, and Northwestern University Information Technology.

Matlab Instructional Seminars  

Presented by MathWorks Application Engineer and Northwestern graduate, Ian McKenna

Join us for complimentary MATLAB instructional seminars. Millions of engineers and scientists worldwide use MATLAB to analyze and design the systems and products transforming our world. Our goal is to help you gain the knowledge to become more efficient and effective using MATLAB.

Data Analysis, Visualization and Automation with MATLAB: Learn how to analyze and visualize data, use desktop tools for editing code, and how to publish and share the results.

Predictive Analytics with MATLAB:  Learn how to evaluate model performance in order to determine the best techniques for your problem and how to rapidly deploy your predictive models into production.

Parallel Computing:  Learn how to use high-level parallel programming constructs to solve and accelerate computationally and data-intensive problems using multicore processors, GPUs, and computer clusters.

Software Carpentry

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This 2-day hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.  The following will be covered: Unix/Bash/Command Line, Python, Git and Github.

About Software Carpentry: Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing.

Last Updated: 10 October 2017

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