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Graduate Specialist Program (New Brunswick Libraries): Workshops - Date order

Home page for the New Brunswick Libraries' Graduate Specialist Program

Fall 2019 Workshop Master Schedule

Spring 2020 workshop master schedule sorted by date (For workshops grouped by topic, click here).

These are pre-Spring Break workshops. More will be offered after Spring Break.

Additional workshops on High Performance Computing are offered by OARC.  See their calendar and resources for more information.

Bring your own laptop to these sessions to get the most out of them!  

Python Basics and Data Exploration (Accelerated 1)

  • Monday, January 27, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

This workshop will be a more deliberate introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions.

Python Basics and Data Exploration (Beginners 1)

  • Tuesday, January 28, 1:00 pm - 2:30 pm, LSM Conference Room (Instructor, Sly Zhong)

This workshop will be an accelerated introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions.

Data Manipulation and Analysis with Python (Accelerated 2)

  • Monday, February 3, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

In this workshop, we will dive into the world of arrays and data frames using the NumPy and pandas libraries. We'll cover data cleaning and pre-processing, joining and merging, group operations, and more. If you work with tabular data, this workshop is for you!

Data Manipulation and Analysis with Python (Beginners 2)

  • Tuesday, February 4, 1:00 pm - 2:30 pm, LSM Conference Room (Instructor, Sly Zhong)

In this workshop, we will dive into the world of arrays and data frames using the NumPy and pandas libraries. We'll cover data cleaning and pre-processing, joining and merging, group operations, and more.

Introduction to Quantitative Text Analysis

  • Tuesday, February 4, 2:00 pm - 3:30 pm, Alexander Library, JetStream, Room 404 (Instructor: Alex Leslie)
  • Thursday, February 6, 10:00 am - 11:30 am, Alexander Library, JetStream, Room 404 (Instructor: Alex Leslie)

This hands-on workshop will introduce participants to the basics of quantitative textual analysis using the R programming language. Participants will each first select a text of their choice from Project Gutenberg (literary or otherwise), which we will then explore through the demonstration of a variety of approaches, including word frequency, distribution, and co-appearance. No coding experience required.

Introduction to GIS with QGIS

  • Wednesday, February 5, 1:30 pm - 3:30 pm, LSM Conference Room

This will be an introductory workshop, no prior GIS knowledge is needed. In this workshop, we will present the basic concepts of Geographic Information Systems. We will discuss file formats, data types, open source data, basic data visualization, attribute tables, projections, and coordinate systems. Time permitting, we will also learn about thematic maps and data classification, and we will explore and interpret some aspects of cartography, such as map layout, text, and color. We will be using QGIS, a freely available GIS application. Please bring a laptop. If you don’t have one, some laptops will be available to borrow.

Introduction to SAS

  • Thursday, February 6, 1:10 pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

This workshop provides an introduction to SAS, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset. 

SAS is a powerful and long-standing system that handles large data sets well, and is popular in the pharmaceutical industry and health sciences, among other applications.

Data Visualization with Python (Beginners 3)

  • Tuesday, February 6, 1:00 pm - 2:30 pm, LSM Conference Room (Instructor, Sly Zhong)

This workshop will continue with Numpy and Panda libraries. Data visualization with matplotlib, a popular plotting library in Python, will also be covered. Turn data into line, bar, scatter plots etc. Environmental Science and Economics data will be used and examples.scikit-learn library. We'll also learn how to do data visualization with matplotlib, a popular plotting library in Python.

Advanced NVivo: Data Visualizations Using NVivo 12

  • Thursday, February 6, 3:30 pm - 5:00 pm, Alexander Library IHL 415 (Instructor, Shari Cunningham)

This workshop focuses on the introduction of a suite of visualizations that help you gain deeper insights from your data by exploring and unearthing patterns, trends and connections.

Data Visualization and Machine Learning with Python (Accelerated 3)

  • Monday, February 10, 2:50-4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

Interested in finding patterns and predicting unknown attribute values in your data? Join us for an overview of machine learning techniques implemented using the scikit-learn library. We'll also learn how to do data visualization with matplotlib, a popular plotting library in Python.

Collecting Twitter Data for Research

  • Tuesday, February 11, 10:00 am - 11:30 am, Alexander Library, Room 413 (Instructor: Francesca Giannetti)
  • Thursday, February 13, 2:00 pm - 3:30 pm, Alexander Library, Room 413 (Instructor: Francesca Giannetti)

This workshop is the first in a two-part series on social media data. Twitter data provide researchers with a real-time view into a wide variety of social and cultural topics. In this workshop, we’ll explore beginning and intermediate tools for collecting social media data from Twitter.

Advanced GIS with QGIS

  • Wednesday, February 12, 1:30 pm - 3:30 pm, LSM Conference Room

In this workshop, we will learn about selection, queries, and spatial joins; and we will cover geoprocessing tools such as dissolve, merge, append, clip, buffer, intersect, union, and erase. We will present address geocoding, and working with street files. Time permitting we will discuss digitizing paper maps, and how to create shapefiles, geoeferencing, and using the editing toolbar. Some prior familiarity with GIS is assumed. We will be using QGIS, a freely available GIS application. Please bring a laptop. If you don’t have one, some laptops will be available to borrow.

R for data analysis: a tidyverse approach

  • Thursday, February 13, 1:10 pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

The session introduces the R statistical software environment and basic methods of data analysis, and also introduces the "tidyverse".  While R is much more than the "tidyverse", the development of the "tidyverse" set of packages, led by RStudio, has provided a powerful and connected toolkit to get started with using R.  Note that graphics and data manipulation are covered in subsequent sessions.

Statistical Inference with Python
  • Monday, February 17, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

In this workshop, we will explore basic principles behind using data for estimation and for assessing theories. The workshop will focus on inference procedures, constructing confidence intervals, and hypothesis testing.

 

Cryptocurrency API, Visualization, and Comparison project 
  • Thursday, February  18,  1:30 pm-3:00 pm, LSM Conference Room (Instructor, Sly Zhong)
Utilizing NumPy, pandas and matplotlib, this workshop will show how to make a program that can compare the price, Log Returns, SMA (Simple Moving Average) of Bitcoin and Ethereum, and predict which one is a better investment choice with Python. A real-time cryptocurrency interactive API will also be introduced in this workshop.
 

Analyzing Social Media Data in R

  • Tuesday, February 18, 10:00 am - 11:30 am, Alexander Library, Room 413 (Instructor: Francesca Giannetti)
  • Thursday, February 20, 2:00 pm - 3:30 pm, Alexander Library, Room 413 (Instructor: Francesca Giannetti)

This workshop is the second of a two-part series. In this workshop, we’ll receive a gentle introduction to the R language and RStudio, the most commonly used integrated development environment for R. We’ll explore a social media dataset using some popular packages of the tidyverse collection, including dplyr and ggplot2.

Introduction to NVivo 

☞ RSVP for the Qualitative Data/NVivo workshops.

  • Thursday, February 20, 3:30 pm - 5:00 pm, Douglass Library Instructional Alcove (Instructor, Shari Cunningham)
  • Thursday, April 16, 3:30 pm - 5:00 pm, Alexander Library IHL 413 (Instructor, Shari Cunningham)

This workshop is intended as a basic introduction to using NVivo, a software that supports qualitative and mixed methods research. The workshop focuses on introducing key mechanisms of the software that may be applied as required by different analytical approaches.

Network Analysis in Gephi

  • Monday, February 24,10:00 am - 11:30 am, Alexander Library, Room 413 (Instructor: Alex Leslie)
  • Tuesday, February 25, 2:00 pm - 3:30 pm, Alexander Library, Room 415 (Instructor: Alex Leslie)

Network analysis is one of the most popular approaches in the digital humanities because it allows us to model relations–between individuals, texts, locations, and more. In this workshop, participants will be introduced to the central concepts of network analysis before learning how to use Gephi, one of the most popular programs for analyzing and visualizing networks.

R graphics with ggplot2 

  • Thursday, February 20, 1:10 pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

The ggplot2 package from the tidyverse provides extensive and flexible graphical capabilities within a consistent framework.  This session introduces the main features of ggplot2. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background.  

Statistical Hypothesis Tests in Python/SAS/R

  • Tuesday, February 25, 1:00 pm-2:30 pm, LSM Conference Room (Instructor, Sly Zhong) 

This workshop delves into a wider variety of basic and most commonly used statistical tests including Null Hypothesis Testing, Critical Value, p-value, Z-test, T-test and Chi-Square Test etc. and how to run those test in different programming languages including Python/R and SAS.

 

Data Science with Python, part 1

  • Monday, February 24, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

This workshop delves into a wider variety of basic supervised learning methods for both classification and regression (Linear Regression, Logistic Regression, Naive Bayes, k-nearest neighbor). In the last part, we will discuss unsupervised learning techniques namely k-Means, PCA. We will apply all techniques on a dataset and compare each of these techniques in terms of accuracy, inference, etc. 

R data wrangling with dplyr, tidyr, readr and more

  • Thursday, February 27, 1:10 pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

Some of the most powerful features of the tidyverse relate to its abilities to import, filter, and otherwise manipulate data.  This session reviews major packages within the tidyverse that relate to the essential data handling steps require before (and during) data analysis.

 

Data Science with Python, part 2

 

  • Monday, March 2, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

This workshop focuses on advanced supervised learning methods for both classification and regression (Decision Tree, Random Forest, Support Vector Machine, Ensemble learning, Neural Network). We will apply all these techniques on a dataset and compare the results of each technique.

 

Interaction with API in Economics 
  • Tuesday, March 3, 1:00 pm - 2:30 pm, LSM Conference Room (Instructor, Sly Zhong) 
An API, or application programming interface, is a common tool for interacting with data on the web. This workshop will present how APIs are used in Finance (Equity and Cryptocurrency) and Economics (FRED) industry.Cryptocurrency) and Economics (FRED) industry.  
 

Approaches to Web Scraping in R

  • Tuesday, March 3, 10:00 am - 11:30 am, Alexander Library, Room 413 (Instructor: Alex Leslie)
  • Thursday, March 5, 2:00 pm - 3:30 pm, Alexander Library, Digital Humanities Lab, Room 406-407 (Instructor: Alex Leslie)

An ever-growing wealth of information can be accessed online, but often there is no easy way to obtain this information for further analysis. This hands-on workshop will introduce a solution to this problem: web scraping, a technique for extracting data and data structures from public websites. Using our browsers and the R programming language, we’ll also explore strategies for handling different kinds of websites. No previous coding experience required.

Introduction to GIS with QGIS

This will be an introductory workshop, no prior GIS knowledge is needed. In this workshop, we will present the basic concepts of Geographic Information Systems. We will discuss file formats, data types, open source data, basic data visualization, attribute tables, projections, and coordinate systems. Time permitting, we will also learn about thematic maps and data classification, and we will explore and interpret some aspects of cartography, such as map layout, text, and color. We will be using QGIS, a freely available GIS application. Please bring a laptop.

  • Wednesday, March 4, 1:30 pm- 3:30 pm, Alexander Library, Jetstream room 4th floor (Instructor: Rahul Dagli)

R for interactivity: an introduction to Shiny

  • Thursday, March 5, 1:10pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

Shiny is an R package that enables the creation of interactive websites for data visualization.   This session provides a brief overview of the Shiny framework, and how to edit and publish Shiny sites in RStudio (with shinyapps.io).  Familiarity with R/RStudio is assumed.

Qualitative Methods Applications

  • Thursday, March 5, 3:30 pm - 5:00 pm, Alexander Library IHL 415 (Instructor, Shari Cunningham)

This workshop introduces hands on practical techniques of how to plan out and conduct small scale pilot studies. This session will  provide an overview of how to create a realistic timeline for a study which includes selecting participants, practical approaches on how to managing sensitive /difficult subjects, and how to ethically and critically connect theory to qualitative analysis using NVivo.ging sensitive /difficult subjects, and how to ethically and critically connect theory to qualitative analysis using NVivo.

Neural Networks

  • Monday, March 9, 2:50 pm - 4:10 pm, Alexander Library, 4th floor, JetStream Room (Instructor, Sanket Badhe)

This workshop describe Neural Network techniques for data analysis.

 

Advanced GIS with QGIS

In this workshop, we will learn about selection, queries, and spatial joins; and we will cover geoprocessing tools such as dissolve, merge, append, clip, buffer, intersect, union, and erase. We will present address geocoding, and working with street files. Time permitting we will discuss digitizing paper maps, and how to create shapefiles, geoeferencing, and using the editing toolbar. Some prior familiarity with GIS is assumed. We will be using QGIS, a freely available GIS application. Please bring a laptop.

  • Wednesday, March 11, 1:30-3:30 pm, Alexander Library, 4th floor Jetstream room (Instructor, Rahul Dagli)

R for reproducible scientific documents: knitr, rmarkdown, and beyond

  • Thursday, March 12, 1:10 pm - 2:30 pm, Alexander Library, 4th floor, JetStream Room  (Instructor, Ryan Womack)

The RStudio environment enables the easy creation of documents in various formats (HTML, DOC, PDF) using Rmarkdown, while knitr allows the incorporation of executable R code to produce the tables and figures in those documents. This session introduces these concepts and other packages and practices supporting reproducibility with the R environment.

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