Events

  • Introduction to Python’s NumPy library

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    This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth, along with related linear algebra and random number capabilities. Some familiarity with Python is expected. The workshop will be done online via Zoom. We will run […]

    GIS Fundamentals – II (Vector and network data models)

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    This is the second workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications, but we will also touch upon the technical aspects. […]

    Introduction to SPSS: Basics of SPSS

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    Each section will go over one chapter from the materials at https://cscar.github.io/workshop-spss/ Section 1: Basics of SPSS (1/20, 10am – 12pm) Section 2: Variables (1/27, 10am – 12pm) Section 3: Data Management (2/3, 10am – 12pm) Section 4: Basic Statistical Analysis (2/10, 10am – 12pm) It is strongly encouraged to have SPSS installed on your […]

    Advanced Graphics Optimization For Data Visualization In Unity3D

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    Modern 3D game engines and computer hardware can render convincing graphics, rivaling that of pre-rendered 3D animation. But video games still require special optimization techniques and tricks. This relates directly to perceived capabilities for data visualization and serious applications: we can generate and render thousands of interactive objects. But what about millions? This workshop will […]

    GIS Fundamentals – I (Coordinate systems)

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    This is the first workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient understanding for applications, but we will also touch upon the technical aspects. […]

    Software Carpentry Workshop @WISE: Shell, R, Git

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    Please note: This is a two day workshop. January 11 and January 12  (*one* registration covering both days) Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills in a supportive & inclusive environment. This hands-on workshop will cover basic concepts […]

  • Spatial regression models

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    This lecture-style workshop will introduce relevant concepts and techniques for modelling cross-sectional data observed on regular (such as remote sensing pixels) or irregular (such as Census polygons) lattice. Such data often exhibits spatial dependence and is common across several fields. We will cover the following topics: motivating examples from time series; spatial random fields and […]

    Using Distill for R Markdown

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    There are a variety of formats available for R markdown beyond 'standard html', one of which is Distill.  Distill is specifically oriented toward presentation of results, and offers a clean look with additional capabilities for citations, marginal exposition, and more.  One can even build an entire website or blog with this format.  This workshop will provide […]

    Introduction to Deep Neural Networks with Keras/TensorFlow

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    Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs, as well as image classification using Convolutional Neural Networks (CNNs). We will also look […]

  • Map making in R

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    The focus of the workshop is twofold: to learn cartography principles for generating single and multivariable choropleth maps, and explore functionalities of R for generating static and interactive web maps. We will use the COVID19 data available at (https://github.com/nytimes/covid-19-data) and combine it with information from Census and other sources to visualize spatial patterns and make […]