Editing Community Data Science Course (Spring 2023)

From CommunityData
Warning: You are not logged in. Your IP address will be publicly visible if you make any edits. If you log in or create an account, your edits will be attributed to your username, along with other benefits.

The edit can be undone. Please check the comparison below to verify that this is what you want to do, and then publish the changes below to finish undoing the edit.

Latest revision Your text
Line 58: Line 58:
=== Microsoft Teams ===
=== Microsoft Teams ===


We'll be using Microsoft Teams for class chat. There are details in the canvas announcements!
We'll be using Microsoft Teams for class chat. More details are {{forthcoming}} soon!


=== Open Labs ===
=== Open Labs ===
Line 117: Line 117:
Be as specific as possible about the data available on the sources you've chosen. I expect that you will have written at least some of the final code that you will use in this course. At the very least, you will have identify the documentation and the API endpoints that are required. If there are libraries that you think may help with access, note them.
Be as specific as possible about the data available on the sources you've chosen. I expect that you will have written at least some of the final code that you will use in this course. At the very least, you will have identify the documentation and the API endpoints that are required. If there are libraries that you think may help with access, note them.


Unless you've talked to us, we expect every person to include at least one visualization in their final project. For the proposal, please include "dummy" versions of these that shows us what the x and y axes are. It's OK (and maybe best!) if these are simple and hand drawn!
If you are planning on create figures or tables, please include "dummy" versions of these that shows us what the x and y axes are. It's OK (and maybe best!) if these are simple and hand drawn!


=== Final Project ===
=== Final Project ===
Line 123: Line 123:
For your final project, I expect you to build on the first two assignments to describe what they have done and what you have found. I'll expect every student to give both:
For your final project, I expect you to build on the first two assignments to describe what they have done and what you have found. I'll expect every student to give both:


# A short presentation (8 minutes max)
# A short presentation (7 minutes)
# A final report that is not more than 4500 words (~18 pages)
# A final report that is not more than 4500 words (~18 pages)


Line 132: Line 132:
==== Final Presentation ====
==== Final Presentation ====


;'''Presentation Date:'''  
:'''Presentation Date:''' At some point during the beginning of the last week of the quarter (the week of May 29). Details will be {{forthcoming}}.
* Presentations need to be shared in the Canvas discussion by '''Monday May 29 at 11:59pm'''
:'''Turning in:''' Details are {{tentative}} but we will very likely ask you upload a video to Canvas and will provide information and links on how to do this.
* Feedback on others presentations need to be posted by '''Thursday June 1 at 11:59pm'''
 
Your presentation should provide the teaching team and your classmates with a very clear idea of what to expect in your final paper. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. I'm going to give you all at least a paragraph of feedback after your talk. This will be an opportunity for me to see a preview of your paper and give you a sense for what I think you can improve. It's to your advantage to both give a compelling talk and to give me a sense for your project.
;'''Turning in:'''  
* Upload your video as a new thread in this [https://canvas.uw.edu/courses/1633288/discussion_topics/8134432 Canvas discussion]


;'''Watching presentations and feedback:'''
The current plan is:
* We're expecting ''every'' person in the class to watch ''every'' presentation. It should take about 2 hours 30 minutes.
* Leave substantive feedback (see 5-question list below as a guide to feedback) by replying to the threads of the people in [https://teams.microsoft.com/l/message/19:a289c7b44b704149a725047dcafc814d@thread.tacv2/1684191632538?tenantId=f6b6dd5b-f02f-441a-99a0-162ac5060bd2&groupId=189ea783-b3e2-4b4e-83ce-74ebc15db6a5&parentMessageId=1684191632538&teamName=Community%20Data%20Science%20(Spring%202023)&channelName=Final%20Projects&createdTime=1684191632538&allowXTenantAccess=false your final presentation group] [requires Teams access]. We're expecting that you should spend about 15 minutes writing up meaningful feedback for these people. This should take about 90 minutes.
* Leave short feedback (spending 1 minute or so is fine) for everybody who is ''not'' in your presentation group. Saying you love their work is great, but the truest expression of love in data science is intellectual engagement with someone's hard work. Ask a question, make a connection to other ideas and work, or point out a place to dig deeper.


;Length: All presentations will need to be '''a maximum of 8 minutes long'''. Do not exceed 8 minutes and 0 seconds and don't edit your video to speed it up if you go too long. Concisely communicating an idea in the time allotted is an important skill in its own right!
;Length: All presentations will need to be '''a maximum of 7 minutes long'''. Do not exceed 7 minutes and 0 seconds; don't edit your video to speed it up if you go too long. Concisely communicating an idea in the time allotted is an important skill in its own right.


;Slides: You are encouraged to use slides for your talk. Please keep in mind that your slides are meant to be additive, not a teleprompter.
;Slides: You are encouraged to use slides for your talk. Please keep in mind that your slides are meant to be additive, not a teleprompter.


;Recording your talk: There are a range of options for recording your talk. If all else fails, you can join a Zoom room by yourself, share your screen, and record the sessions. It's been working for the class all quarter long so it'll probably work for you too!
;Modality: We will not meet during the final week due to the Memorial Day holiday. As a result, we plan to conduct these virtually.
 
Your presentation should provide the teaching team and your classmates with a very clear idea of what to expect in your final paper. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. The teaching team will provide you with substantial feedback on your presentation. This will be an opportunity for me to see a preview of your paper and give you a sense for what I think you can improve. It's to your advantage to both give a compelling talk and to give me a sense for your project.
 
Here is a list of questions to think about both when providing in your feedback and when structuring your talk:
 
# In your own words, what research question did you hear the presenter answer? What are they trying to communicate? How well did they answer their question or achieve their goals? Did you find the answer compelling? Why or why not?
# Be critical. What problems, challenges, or limitations do you see with the way that the presenter is trying to measure things? What are the risks or threats to the validity of the work?
# How would you improve the work? What additional sort of data do you think could be helpful? What sort of additional analysis or visualization would be helpful? What additional interpretation would be helpful?
# If you saw this as a YouTube video or retweeted on Twitter, what sort of questions would you leave in the comments?
# If you were doing this project and presenting it to a supervisor, how would they respond? What changes would you want to make to address this audience a result? What if you were presenting it a colleague, collaborator or friend?


==== Final Paper (and Code!) ====
==== Final Paper (and Code!) ====


:'''Due Date:''' Thursday June 8 at 11:59 p.m.
:'''Due Date:''' Thursday June 8 at 11:59 p.m.
:'''Turning in:''' Turn in a PDF of your paper to [https://canvas.uw.edu/courses/1633288/assignments/8231894 the Canvas dropbox]; Upload all your code into the [https://github.com/kayleachampion/spr23_CDSW/tree/main/final_project_code final_project_code directory in the class Github repository].
:'''Turning in:''' Turn in a PDF of your paper to [https://canvas.uw.edu/courses/1633288/assignments/8231894 the Canvas dropbox]; Details on how to turn in your code will be {{forthcoming}}.


Your final project should include detailed information on:
Your final project should include detailed information on:
Line 177: Line 162:
Keep in mind that most stories on Five Thirty Eight are under 1000 words and I'm giving up to 4,500 words to show me what you've learned. As a result, you should do ''more'' than FiveThirtyEight does in a single story. You can ask and answer more questions, you can provide more background, context, and justification, you can provide more details on your methods and data sources, you can show us more graphs, you can discuss the implications of your findings more. Use the space I've given you to show off what you've done and what you've learned!
Keep in mind that most stories on Five Thirty Eight are under 1000 words and I'm giving up to 4,500 words to show me what you've learned. As a result, you should do ''more'' than FiveThirtyEight does in a single story. You can ask and answer more questions, you can provide more background, context, and justification, you can provide more details on your methods and data sources, you can show us more graphs, you can discuss the implications of your findings more. Use the space I've given you to show off what you've done and what you've learned!


Finally, you should also share with me the full Python source code you used to collect the data as well as the data set itself. Your code alone will not form a large portion of your final grade. Rather, I will focus on the degree to which you have been successful at answering the ''substantive'' questions you have identified.
Finally, you should also share with me the full Python source code you used to collect the data as well as the data set itself. Your code along will not form a large portion of your final grade. Rather, I will focus on the degree to which you have been successful at answering the ''substantive'' questions you have identified.


Visualization is critical to storytelling, so 25% of your grade for this project will be determined by the visualizations and tables in your report. Good visualizations should "stand alone" and motivate the core results in your paper all by themselves. A good question to keep in mind is "could I tell this story with the visualizations and a tweet?"
Visualization is critical to storytelling, so 25% of your grade for this project will be determined by the visualizations and tables in your report. Good visualizations should "stand alone" and motivate the core results in your paper all by themselves. A good question to keep in mind is "could I tell this story with the visualizations and a tweet?"
Line 188: Line 173:


== Grades ==
== Grades ==
Assignments will typically be graded as either complete (full credit) or incomplete (no credit) or on the UW 4.0 grade scale. As detailed and linked elsewhere on the syllabus, I have provided [[User:Benjamin Mako Hill/Assessment|detailed rubrics on how I approach assessment]] for writing, for participation, and in general.


Assignments will accrue to your final grade in the following way:
Assignments will accrue to your final grade in the following way:
Line 411: Line 394:


Today we'll (finally!) focus on using a module called <code>pandas</code> that provides spreadsheet like functionality within Python.
Today we'll (finally!) focus on using a module called <code>pandas</code> that provides spreadsheet like functionality within Python.
'''Class session:'''
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8078bce8-61bf-4b3d-8bf5-affd0130c1a7 Video of announcements and week 6 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a815f1ce-ded8-4972-9bb0-affd0130c1a6 Video of week 7 lecture on pandas] [Requires Canvas Access]
* [[/Week 7 lecture notes]]
* Notebooks from the lecture including:
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/week_7_lecture_as_delivered-2023-05-08.ipynb Week 7 lecture notebook] which is the notebook I created in class
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/week_7_lecture_prework-2023-05-08.ipynb Week 7 lecture notebook (prework)] which is most of the same content but it is the version I created before class
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week7/02-analyze_rock_band_data-pandasify.ipynb Wikipedia revisions pandas-ified] which is a modification of the <code>02-analyze_rock_band_data-pandasify.ipynb</code> notebook I created last week but which is modified to output pandas data.


'''Assignment Due:'''
'''Assignment Due:'''
Line 435: Line 408:
=== Week 8: May 15 ===
=== Week 8: May 15 ===


We'll be transitioning into a focus on the final projects and trying to build time into class to make real progress on the programming and data collection part of your final projects.
Today we'll be introducing two additional web APIs in parallel. We'll run a poll of the class to get a sense of what folks want to learn but we're considering Yelp, Reddit, Twitter, and data.seattle.gov.




'''Class session:'''
'''Class session:'''


* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bb9b5451-6d22-4e70-ac30-b00500463da4 Video of announcements and week 7 programming challenges] [Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8078bce8-61bf-4b3d-8bf5-affd0130c1a7 Video of announcements and week 6 programming challenges] [Requires Canvas Access]
* <strike>[https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=322d5481-254f-4df4-929d-b00500463da3 Video of the second part of the class with final presentations overview]</strike> [Appears to be Basically broken; Requires Canvas Access]
* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a815f1ce-ded8-4972-9bb0-affd0130c1a6 Video of week 7 lecture]
 
* [[/Week 7 lecture notes]]
<!-- * Notebooks from the lecture including:
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/01-collect_rock_bands_json.ipynb Week 6 lecture notebook Wikipedia part 1] which handles data collection
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/02-analyze_rock_band_data.ipynb Week 6 lecture notebook Wikipedia part 2] which handles data analysis
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/yelp_business_search-module.ipynb Week 6 lecture notebook Yelp (module)] which uses the [https://github.com/lanl/yelpapi yelpapi] Python module
** [https://github.com/kayleachampion/spr23_CDSW/blob/main/curriculum/week6/yelp_business_search-module.ipynb Week 6 lecture notebook Yelp (direct)] which uses API directly and is only here so you can see how this would work without a module so you get a sense for what the module is doing
-->
'''Resources:'''
'''Resources:'''


Line 457: Line 436:
* Let's discuss remaining schedule
* Let's discuss remaining schedule
* Go over the [[/Week 7 coding challenges]]
* Go over the [[/Week 7 coding challenges]]
* We'll talk in some depth about the [[#Final Presentation]]
* [[/Week 8 lecture]]
* Introduce the [[/Week 8 coding challenges]]
* Project time—We'll work through projects
* Project time—We'll work through projects


Line 466: Line 446:
'''Assignment Due:'''
'''Assignment Due:'''


* Upload your complete data collection code to the [https://github.com/kayleachampion/spr23_CDSW/tree/main/week8-homework week8-homework directory] in the Github repository and be ready to talk about it in class!
* Readings {{tbd}}
* Finish and turn in your [[/Week 8 coding challenges]] (Due Sunday before class)


'''Class schedule:'''
'''Class schedule:'''


* Project time—We'll check in on projects and walk through folks data collection code in two groups
* Let's discuss remaining schedule
* We'll do three topics in parallel: (1) ChatGPT API with Josh; (2) AI/ML for classification with Kaylea, and (3) statistics with Mako.
* Go over the [[/Week 8 coding challenges]]
* [[/Week 9 lecture]]
* Project time—We'll work through projects
 
'''Resources:'''
 
* Visualization dos and don'ts. We'll discuss the European Environmental Agency's [https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts list of advice for making charts]. **I will refer to this guide as a grade your final projects.**
* Two options for remainder of class. You can work through this introductory guide to visualization in python or you can work on your final project. I'll be here to answer any questions.
* Self-guided visualization tutorial in python. [https://raw.githubusercontent.com/guyrt/teaching/master/2019/Com520B/VisualizationNotebook.ipynb Download here]. Save the file in a new directory in your desktop and open it with Jupyter Notebook. (If you are on Windows, you may run into an issue with missing path variables. [https://stackoverflow.com/questions/52821162/jupyter-notebook-failed-to-load-dll This SO post helped me solve it.])


=== Week 10: May 29 (NO MEETING) ===
=== Week 10: May 29 (NO MEETING) ===
Please note that all contributions to CommunityData are considered to be released under the Attribution-Share Alike 3.0 Unported (see CommunityData:Copyrights for details). If you do not want your writing to be edited mercilessly and redistributed at will, then do not submit it here.
You are also promising us that you wrote this yourself, or copied it from a public domain or similar free resource. Do not submit copyrighted work without permission!

To protect the wiki against automated edit spam, we kindly ask you to solve the following CAPTCHA:

Cancel Editing help (opens in new window)

Templates used on this page: