Editing Community Data Science Course (Spring 2016) (section)

== Schedule ==

=== Week 1: March 30 ===

'''Readings:'''

* Python for Informatics: [http://www.pythonlearn.com/html-009/book001.html Preface] and [http://www.pythonlearn.com/html-009/book002.html Chapter 1  Why should you learn to write programs?]

'''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.
* [[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_%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:'''

* Have a working python environment on your personal laptop.
* Have written your first program in the python language.

[http://goo.gl/forms/KO9Kyc9nqN Poll]

=== Week 2: April 6 ===

'''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]].

'''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 ===

'''Assignment Due:'''

* [[#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.

'''Resources:'''

* [[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 ===


'''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 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.