Editing Community Data Science Course (Spring 2017)
From CommunityData
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 1: | Line 1: | ||
:'''Community Data Science: Programming and Data Science for Social Media''' | :'''Community Data Science: Programming and Data Science for Social Media''' | ||
:''' | :'''COM597G''' - Department of Communication | ||
:'''Instructor:''' [http://guyrt.github.com Richard Thomas (Tommy) Guy] | :'''Instructor:''' [http://guyrt.github.com Richard Thomas (Tommy) Guy] | ||
:'''Course Website''': We will use Canvas for | :'''Course Website''': We will use Canvas for [https://todo Announcements], [https://todo Assignments], and [https://todo discussion]. Everything else will be linked on this page. | ||
:'''Course Catalog Description:''' | :'''Course Catalog Description:''' | ||
Line 16: | Line 16: | ||
As part of the class, participants will learn to write software in Python to collect data from web APIs and process that data to produce numbers, hypothesis tests, tables, and graphical visualizations that answer real questions. The class will be built around student-designed independent projects. Every student will pick a question or issue they are interested in pursuing in the first week and will work with the instructor to build from that question toward a completed analysis of data that the student has collected using software they have written. | As part of the class, participants will learn to write software in Python to collect data from web APIs and process that data to produce numbers, hypothesis tests, tables, and graphical visualizations that answer real questions. The class will be built around student-designed independent projects. Every student will pick a question or issue they are interested in pursuing in the first week and will work with the instructor to build from that question toward a completed analysis of data that the student has collected using software they have written. | ||
This is not a computer science class and I am not going to be training you to become professional programmers. This introduction to programming is intentionally quick and dirty and is focused on what you need to get things done. | This is not a computer science class and I am not going to be training you to become professional programmers. This introduction to programming is intentionally quick and dirty and is focused on what you need to get things done. If you want to become a professional programmers, this is probably not the right class. If you want to learn about programming so that you can more effectively answer questions about social media by writing your own software and by managing and communicating more effectively with programmers, you are in the right place. | ||
I will consider this class a complete success if, at the end, every student can: | I will consider this class a complete success if, at the end, every student can: | ||
Line 56: | Line 55: | ||
:'''Maximum Length:''' 600 words (~2 pages double spaced) | :'''Maximum Length:''' 600 words (~2 pages double spaced) | ||
:'''Due Date:''' Week 3 | :'''Due Date:''' Week 3 | ||
:'''Drop box:''' TODO on canvas | |||
In this assignment, you should identify an area of interest, at least 2 | In this assignment, you should identify an area of interest, at least 2 source domains with relevant data, and at least 3-4 questions that you plan to explore. I am hoping that each of you will pick an area or domain that you are intellectually committed to and invested in (e.g., in your business or personal life). You will be successful if you describe the scope of the problem and explain why you think the data sources you've identified are relevant. | ||
I will give you feedback on these write-ups and will let you each know if I think you have identified a questions that might be too ambitious, too trivial, too broad, too narrow, etc | I will give you feedback on these write-ups and will let you each know if I think you have identified a questions that might be too ambitious, too trivial, too broad, too narrow, etc. | ||
=== Final Project Proposal === | === Final Project Proposal === | ||
Line 87: | Line 87: | ||
I expect that your reports will include text from the first two assignments and reflect comprehensive documentation of your project. Each project should include: (a) the description of the question you have identified and information necessary to frame your question, (b) a description of the how you collected your data, (c) the results, (d) a description of the scope or limitations of your conclusion. | I expect that your reports will include text from the first two assignments and reflect comprehensive documentation of your project. Each project should include: (a) the description of the question you have identified and information necessary to frame your question, (b) a description of the how you collected your data, (c) the results, (d) a description of the scope or limitations of your conclusion. | ||
A successful project will tell a compelling, | A successful project will tell a compelling story and will engage with, and improve upon, the course material to teach an audience that includes me, your classmates, and Comm Lead students taking this class in future years how to take advantage of community data science more effectively. The very best papers will give us all a new understanding of some aspect of course material and change the way I teach some portion of this course in the future. | ||
==== Paper and Code ==== | ==== Paper and Code ==== | ||
Line 109: | Line 109: | ||
==== Presentation ==== | ==== Presentation ==== | ||
Your presentation should provide me 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 | Your presentation should provide me 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. 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. | ||
;Timing: All presentations will need to be '''a maximum of 7 minutes long'' with additional 2-3 minutes for questions and answers. Timing is going to be tight and I'm going to set an alarm and stop presentations that go too long. Concisely communicating an idea in the time allotted is an important skill in its own right. | ;Timing: All presentations will need to be '''a maximum of 7 minutes long'' with additional 2-3 minutes for questions and answers. Timing is going to be tight and I'm going to set an alarm and stop presentations that 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 but I will need your slides ahead of class. See link at top of this section | ;Slides: You are encouraged to use slides for your talk but I will need your slides ahead of class. See link at top of this section. | ||
=== Participation === | === Participation === | ||
Line 133: | Line 133: | ||
== Schedule == | == Schedule == | ||
=== Week 1: March 30 === | === Week 1: March 30 === | ||
Line 144: | Line 142: | ||
'''Class Schedule:''' | '''Class Schedule:''' | ||
* Quick introductions — Be ready to introduce yourself and describe your interest and goals in the class. | |||
* Class overview and expectations — We'll walk through this syllabus. | * Class overview and expectations — We'll walk through this syllabus. | ||
* [[Community_Data_Science_Course_% | * [[Community_Data_Science_Course_%28Spring_2016%29/Day_1_Exercise|Day 1 Exercise]] — You'll install software including the Python programming language and run through a series of exercises. | ||
* [[Community_Data_Science_Course_% | * [[Community_Data_Science_Course_%28Spring_2016%29/Day_1_Tutorial|Day 1 Tutorial]] — You'll work through a self-guided tutorial introducing you to some basic concepts. When you're done, you'll meet with a member of the teaching team and we'll check you off. | ||
'''By the end of class you will:''' | '''By the end of class you will:''' | ||
Line 156: | Line 151: | ||
* Have a working python environment on your personal laptop. | * Have a working python environment on your personal laptop. | ||
* Have written your first program in the python language. | * Have written your first program in the python language. | ||
[http://goo.gl/forms/KO9Kyc9nqN Poll] | |||
=== Week 2: April 6 === | === Week 2: April 6 === | ||
Line 161: | Line 158: | ||
'''Assignment Due (nothing to turn in):''' | '''Assignment Due (nothing to turn in):''' | ||
* Finish setup, tutorial and code academy in the [[Community Data Science Course (Spring 2016)/Day 1 Exercise|week 01 exercises]]. | * Finish setup, tutorial and code academy in the [[Community Data Science Course (Spring 2016)/Day 1 Exercise|week 01 exercises]]. | ||
''' | '''Readings:''' | ||
* | * Python for Informatics: [http://www.pythonlearn.com/html-009/book003.html Chapter 2 Variables, expressions and statements] and [http://www.pythonlearn.com/html-009/book004.html Chapter 3 Conditional execution] | ||
'''Class Schedule:''' | |||
* | * [[Community Data Science Course (Spring 2016)/Day 2 Lecture|Day 2 Lecture]] — Interactive class lecture including a review of material from last week and new material including loops, lists, and modules. | ||
* Project time — We'll begin working on the [[wordplay]] independent projects independently or in small groups with assistance from the teaching team. | |||
''' | '''Resources:''' | ||
* | * [[Community Data Science Course (Spring 2016)/Day 2 Plan|Day 2 Plan]] | ||
* | * [[Community Data Science Course (Spring 2016)/Day 2 Coding Challenges|Day 2 Coding Challenges]] | ||
[ | [http://goo.gl/forms/xcwx6mDDZV Feedback Poll] | ||
=== Week 3: April 13 === | === Week 3: April 13 === | ||
Line 189: | Line 180: | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
Final project | * [[#Final_Project_Ideas|Final Project Ideas]] [[https://canvas.uw.edu/courses/1039305/assignments/3252050 Turn in on Canvas]] | ||
* Code solving challenges in [[wordplay]] project. This will ''not'' be graded, but I want to get a sense for where everyone is at. [[https://canvas.uw.edu/courses/1039305/assignments/3252042 Turn in on Canvas]] | |||
'''Class Schedule:''' | |||
''' | |||
* | * Review and Lecture — We'll walk through answers to the assignments for last week as a group. | ||
* Project time — We'll begin working on a series of project based on the [[Baby_names]] project. | |||
* Project time — We'll begin working on a series of project based on the [ | |||
'''Resources:''' | '''Resources:''' | ||
* [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far including today. | * [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far including today. | ||
* [[Community Data Science Course (Spring 2016)/Day 3 Plan|Day 3 Plan]] | |||
* [[Community Data Science Course (Spring 2016)/Day 3 Coding Challenges|Day 3 Coding Challenges]] | |||
=== Week 4: April 20 === | === Week 4: April 20 === | ||
'''Assignment Due (nothing to turn in):''' | |||
* | |||
** [ | '''Class Schedule:''' | ||
* | |||
* Data Viz: let's walk through an example. | |||
* Review and Lecture — We'll walk through answers to the assignments for last week as a group. Then we'll introduce APIs. | |||
* Project time — We'll begin working on a series of projects based on Wikipedia's API. | |||
'''Resources:''' | |||
* [[Community Data Science Course (Spring 2016)/Day 4 Plan|Day 4 Plan]] | |||
* [[Community_Data_Science_Course_(Spring_2016)/Day_4_Lecture|Day 4 Lecture]] | |||
* [[Community Data Science Course (Spring 2016)/Day 4 Coding Challenges|Day 4 Coding Challenges]] | |||
* [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far. | |||
=== Week 5: April 27 === | |||
''' | '''Assignment Due (nothing to turn in):''' | ||
'''Class Schedule:''' | |||
* Review and Lecture — We'll walk through answers to the assignments for last week as a group. Then we'll introduce APIs. | |||
* Project time — We'll begin working on a series of projects based on Wikipedia's API. | |||
''' | '''Resources:''' | ||
* [[Community Data Science Course (Spring 2016)/Day 5 Plan|Day 5 Plan]] | |||
* [[Community_Data_Science_Course_(Spring_2016)/Day_5_Lecture|Day 5 Lecture]] | |||
* [[Community Data Science Course (Spring 2016)/Day 5 Coding Challenges|Day 5 Coding Challenges]] | |||
* [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far. | |||
=== Week 6: May 4 === | |||
'''IMPORTANT: Class will be starting at 6:30 not 6:00 for May 4.''' | |||
'''Assignment Due:''' Final project proposal. | |||
[[https://canvas.uw.edu/courses/1039305/assignments/3270775 Turn in on Canvas]] | |||
''' | ''' Class Schedule:''' | ||
* | * Review and Lecture - We'll review all of the material from last week. No new material this week: I want to make sure you get caught up to date on working APIs in general. | ||
* | * Project time - Two options. | ||
** Option 1: Continue working on the Wikipedia questions. I've added a few new questions. | |||
** Option 2: Start working on your final project with the help of a mentor. Use this time to cover questions like data access. If you can already download your data, great! Start thinking about analysis questions and visualizations. | |||
* [[Community Data Science Course (Spring 2016)/Day 6 Plan|Day 6 Plan]] | |||
* [[Community_Data_Science_Course_(Spring_2016)/Day_6_Coding_Challenges|Day 6 Challenge]] | |||
* [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far. | |||
=== Week 7: May 11 === | |||
''' | '''Assignment Due:''' | ||
* | * Finish the [[Twitter authentication setup]] to request keys necessary to begin using the Twitter API. | ||
''' Class Schedule:''' | |||
' | * Review and Lecture - we'll review the exercise from last week. | ||
** Samples | |||
* One new thing to learn: opening and reading files. | |||
* Lecture - introduce the [https://dev.twitter.com/overview/documentation|Twitter API] | |||
** Sample code is [[Community_Data_Science_Course_(Spring_2016)/Day_6_Lecture|here]] | |||
* Project time - Three options. | |||
** Option 1: If you are working on Twitter, I would encourage you to work on the [[Community_Data_Science_Workshops_(Spring_2016)/Day_2_Projects/Twitter|getting Twitter data]] exercises. | |||
** Option 2: If you are not working on Twitter, I would encourage you to work on the [[Community_Data_Science_Workshops_%28Spring_2016%29/Day_3_Projects/Twitter|Using Twitter Data]] exercises. | |||
** Option 3: Take this time to get help with your projects (and do one of the other options this week). | |||
* | ''' Resources ''' | ||
* Twitter: [https://mako.cc/teaching/2015/cdsw-autumn/twitter-api-cdsw.zip] | |||
=== Week | === Week 8: May 18 === | ||
''' | ''' Class Schedule:''' | ||
' | * Talk about final presentations. | ||
* Review last week's Twitter assignments (30 mins) | |||
* Lecture (without code!) about what makes a good metric. | |||
* Project time. Take this time to get help with and/or work on your projects. | |||
== Administrative Notes == | == Administrative Notes == | ||
Line 284: | Line 287: | ||
=== Office Hours === | === Office Hours === | ||
Because this is an evening degree program and I understand you have busy schedules that keep us away from campus during the day, I will not hold regular office hours. In general, I | Because this is an evening degree program and I understand you have busy schedules that keep us away from campus during the day, I will not hold regular office hours. In general, I will be available to meet before class. Please contact me on email to arrange a meeting then or at another time. | ||
=== Disability Accommodations Statement === | === Disability Accommodations Statement === |