| Format | Event Recording |
|---|---|
| Level | Beginner |
| Software | Adobe Illustrator, Microsoft Excel |
| Topic | Data Visualization, Public Scholarship, Research Dissemination |
| Workshop/Event Series | Data Analysis Support Hub |
Creating High-Impact Figures with Adobe Illustrator
Learn how to turn your Excel data into high-impact figures with Adobe Illustrator. This introductory-level workshop will teach the fundamentals of Adobe Illustrator and how to use this software to modify SVG (Scalable Vector Graphics) files exported from Excel.
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Intro to Business Analyst Online
The ArcGIS Business Analyst Web App (BAO) is a web application that allows users to map and analyze business, demographic, and consumer spending data. Users are also able to export data, maps, and reports to Microsoft Excel, PDF, or image formats.
This workshop contains several brief video tutorials from Esri to help you get started using the program.
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Machine Learning with R: SVM Classification
Support Vector Machine (SVM) is a supervised machine learning algorithm used for both classification and regression. This workshop will only cover the theoretical and practical parts of SVM classification as SVM is mostly used in classification problems. After the introduction, participants will receive hands-on training in the implementation of SVM classification in R, as well as training and testing datasets and setting up tuning and kernal parameters.
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Intro to Designing Effective Data Visualizations
An effective data visualization makes all the difference. Learn to present your research in its best light at this beginner-friendly workshop on the basic design principles and best practices that can be applied across different data visualization software and tools.
Participants will learn how to plan for visualizations from concept to design output, and how to incorporate thinking about dissemination of data as scholars progress in their research.
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Machine Learning with R: Random Forest Classification Approach
The Random Forest is a powerful algorithm used for classification in the industry. The classification algorithm consists of many decision trees to get more accurate predictions. This workshop will go over the theoretical part of Random Forest, then provide attendees with hands-on training on conducting Random Forest classification, training the data, testing accuracy, and working with tuning parameters.