Course Information
| Session |
|---|
| Credits | 1.5 CEUs or 15 PDHs |
|---|---|
| Registration dates | We accept registrations through the first week of classes, unless enrollment is full, and unless the class was canceled before it started due to low enrollment. |
Python for Librarians
$200.00
Dates: June 6 - July 3November 7 - December 4
February 6 - March 5
May 1 - May 28
Credits: 1.5 CEUs or 15 PDHs
We often are told ‘learn to code’ but not given a clear purpose or direction to realize this goal. This is especially true for workers in the Library field. This course will attempt to address this challenge by providing a great introduction to data science aimed at all learners. Participants will be introduced to the Python programming language and how it can be used to analyize data. This includes organizing and writing code in Jupyter Notebooks, manipulating data with the Pandas, visualizing data with the Matplotlib, and making predictions with data using the scikit-learn library. No previous programming experience is required or expected. Exercises will be drawn from topics that resonate with the daily work of Librarians and those in related fields. For example, participants will learn how to analyze a quantity of Sci Hub usage data, and will examine DOI data harvested from the Crossref API. No software installation will be required to participate in this class; all programming work will be done using the online Google Colab environment.
Course Description
We often are told ‘learn to code’ but not given a clear purpose or direction to realize this goal. This is especially true for workers in the Library field. This course will attempt to address this challenge by providing a great introduction to data science aimed at all learners. Participants will be introduced to the Python programming language and how it can be used to analyze data. This includes organizing and writing code in Jupyter Notebooks, manipulating data with the Pandas, visualizing data with the Matplotlib, and making predictions with data using the scikit-learn library. No previous programming experience is required or expected. Exercises will be drawn from topics that resonate with the daily work of Librarians and those in related fields. For example, participants will learn how to analyze a quantity of Sci Hub usage data, and will examine DOI data harvested from the Crossref API. No software installation will be required to participate in this class; all programming work will be done using the online Google Colab environment.
Tim Ribaric
Tim Ribaric received his MLIS from The University of Western Ontario in 2006 and his MSC in Computer Science from Brock University in 2017. He has been working at The Brock University Library since 2006 and is presently the Acting Head of the Digital Scholarship Lab and Map Data GIS Library. He has published and presented on many different topics including: labour issues, effectively utilizing technology in the library environment, and cracking cryptographic systems. All of his coding projects can be found on GitHub. His website and blog can be found at https://elibtronic.github.io/
How to Register
To enroll yourself or other participants in a class, use the “Register” button that follows the description of each course. If the “Register” button does not show up, try loading the page in a different web browser. Contact us if you have technical difficulties using our shopping cart system or would like to pay for an enrollment using another method. On the payment page in the shopping cart system, there is a place to add notes, such as the names and email addresses of participants you wish to enroll. We will contact you to request this information in response to your processed payment if you do not include it in the “notes” field. Prior to the start of the workshop, we will send participants their login instructions.Payment Info
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