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 – $300.00
Dates: November 7 - December 4February 6 - March 19
May 1 - June 11
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
Our shopping cart system allows you to pay with a credit card, with PayPal, or to indicate that you'll be sending a check.Alternatively, if it is an institutional payment, we can arrange to invoice you. Contact us by email, and we can make arrangements to suit your institution's business processes.
B. M. –
Terrible. Badly structured and poorly explained course. It’s a waste of time and money. There are far better online course out there and they don’t feel like torture (plus they are much cheaper)
Carla –
Having delivered data/statistical online instruction via Zoom, I understand how difficult it can be to create a learner-focused space that includes a high degree of interactivity. I think it must be even more difficult to do so for an asynchronous workshop–but Tim has done it. Python for Librarians clearly sets out the agenda and goals for the course and for each class. It’s structured using easy-to-access (and free) collaborative tools which can be revisited after the workshop concludes. I particularly appreciated that, in addition to doing the Python-specific lessons, participants were asked to share their challenges and their successes as part of the course requirements. This created a sense of community and camaraderie. Tim was extremely responsive to students’ questions and encouraging where people ran into trouble. If you’re new to programming, I 100% recommend this course. Take your time. And don’t be afraid to ask questions.
Geoff –
I took this course as a middle-aged novice to programming/coding. I definitely did find the course useful as an introduction to Python and what I could do with it. I found the software useful in completing the different tasks and exercises. Tim was always prompt with feedback and help for the times I did get lost (I was taking this course on the other side of the world as well!). I am now progressing with further programming/coding after my introduction here.
Gopal Dutta –
Really enjoyed the course. I’ve done a few programming/code courses before and have now understood that you don’t need to understand everything straightaway, and it’s OK to get an answer without knowing the exact “why”. The teaching/learning style (workbooks to go through, comments from the tutor, forum to ask questions) works well for me and I’ve already booked onto another Library Juice course. Tim was very supportive and helpful, beyond the confines of the course. I was able to apply the knowledge I gained to an actual existing work problem (analysing the spread of character counts within a field, to help with deciding how to structure a new databases page).
Chris Dillon –
Except for learning a small amount of PHP about 15 years ago, this was my introduction to programming.
It is a fast-moving course, also covering interesting topics such as data analysis and machine learning.
The first week was challenging, as it was necessary to find a learning methodology that worked.
The weekly homeworks took a problem-solving approach. This was fun, as it was effectively a matter of solving puzzles. If I got stuck, it was important to move on to the next one and come back. I made myself comment on nearly every line of code as a way of understaning what was going on and revealing things I didn’t get. This worked well with Tim Ribaric, the course tutor, as he could see where I had wandered off and gently nudge me back on the path.
This seems to be an unusual Python course in that most courses have a high percentage of number-crunching. For me, that is peripheral, and the fact that this was library-centred was a huge plus.
Tim provided useful practical resources for the next stage of learning and tips for setting up Python in various environments.
tm3000 –
I found the course very challenging and also very relevant to my work. It was certainly different to any other course I’d been on, as each student works on the colab workalong documents and assignments at their own pace, without needing to commit to meeting up at specific times. This suited me very well – and there was a chance for the group to swap notes and tips.
Tim offered a lot of support – in spite of the time differences – and our group was from the same institution so we discussed the course actively (and probably will in the future).
The difficulty with coding is there are probably things that you know you *want* to do but can’t, because you don’t have the exact vocabulary. This course encourages the student to keep on trying until something works and it is quite satisfying when a graph or pie chart appears in the way that you want it! It does require some determination, particularly in the first couple of weeks, to make python work, but it is definitely worth persevering.
The collection of colab notebooks (which are free) will be a useful post-course resource and I am now thinking of ways of using python for future projects.
Dharini Baskaran –
The first three sessions of the class was great. However, during the last session, I found myself quite lost. Not sure if it was because of the examples or because I found a big jump in the learning. But I feel the last session could have been split up into two parts and students could be eased into it to learn the concept.