October 2019
Introduction to NumPy (Python)
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…
Geometric Network Analysis
This workshop will cover GIS concepts and techniques for analyzing geometric networks embedded in geographical space. We will mainly focus on road network, but the ideas and techniques apply to…
Back to a Future: Asynchronous Computing with futures in R
Asynchronous computing is an umbrella term encompassing parallel and concurrent computational programs in which some tasks can be executed without a strict sequential order. A future is a programming abstraction for a value…
Mediation Models: A demonstration using multiple packages
Mediation models are commonly applied in a variety of modeling settings, and people will typically flock to tools specific to structural equation modeling like Mplus or Amos for analysis. However,…
Introduction to Performance Analysis of Scientific Software
We all had this: "My program is too slow". We all have heard: "Use Fortran and C++, they are fast." But will it really help? We all have heard also:…
November 2019
Intro to SQL
Ever want to know how to communicate with a database? You need to know SQL, a standard programming language for working with relational database management systems in data warehouses or…
Introduction to Deep Neural Networks with Keras/TensorFlow
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…
Android Application Development: An Overview
Mobile app development is one of the biggest new industries of the last decade. As of 2017, Google and Apple (the creators of Android and iOS, respectively) confirmed a combined…
Improving the Performance of Scientific Software
This is a continuation of the workshop "Introduction to performance analysis of scientific software". Now, we know how to measure overall performance of our software and can make a good…
Stata 16 New Data Management Features
Audience: Stata users familiar with data management who want an overview of the new data management features introduced in Stata 16. We'll cover the two main data management features introduced…
Rcpp: Integrating C++ into R
The Rcpp package for R provides “seamless R and C++ integration”. In this workshop, we will discuss the use of Rcpp to speed up existing R code by rewriting slow functions…