DS4UX (Spring 2016)/Schedule

Week 1: March 28
Day 1 plan


 * Assignments due
 * fill out the pre-course survey


 * Agenda
 * Quick introductions — Be ready to introduce yourself and describe your interest and goals in the class.
 * Why Programming and Data Science for UX Research? — What this course is about
 * Class overview and expectations — We'll walk through this syllabus.
 * Group formation — We'll assemble in our peer programming groups for the first time.
 * Installation and setup — You'll install software including the Python programming language and run through a series of exercises.
 * Interactive lecture: programming concepts 1
 * Self-guided tutorial and exercises — You'll work through a self-guided tutorial to practice the basic concepts we introduced in the lecture.


 * Homework
 * Complete Self-guided tutorial and exercises (if you didn't finish this in class).
 * Complete CodeAcademy lessons


 * Resources
 * Python for Informatics Chapter 1

Week 2: April 4
Day 2 plan


 * Agenda
 * Review concepts we covered last week
 * Interactive lecture: programming concepts 2
 * Peer programming exercise: Baby Names (download)


 * Homework
 * Complete the second set of CodeAcademy lessons
 * Work on the Week 2 coding challenges
 * Create a Wikimedia account & submit your username using 


 * Resources
 * go here

Week 3: April 11
Day 3 plan


 * Class schedule
 * Interactive lecture: creating your own functions
 * Day 3 lecture - working with web data 1 (APIs)
 * Peer programming: Practice with API sandboxes
 * Interactive lecture: requesting data from an API using Python


 * Homework
 * Day 3 coding challenges


 * Resources
 * go here

Week 4: April 18
Day 4 plan


 * Class schedule
 * Day 4 lecture - working with web data 2 (SQL)
 * introduction to the Wikipedia database
 * programming concepts 4
 * SQL queries
 * advanced API queries


 * final project discussion 1
 * data sources
 * research questions
 * outline of project idea and project plan deliverables


 * Exercises
 * MYSQL queries with Quarry
 * SOQL queries with Hurl.it and Python


 * Homework
 * Python quiz #4
 * Day 4 coding challenges


 * Resources
 * go here

Week 5: April 25
Day 5 plan


 * Assignments due
 * Final project idea


 * Class schedule
 * Day 5 lecture - visualizing data
 * Introduction to Jupyter notebooks
 * Jupyter notebooks 1
 * importing data with SQL and API queries
 * data manipulation with Jupyter


 * Exercises
 * visualize Seattle building permit data


 * Homework
 * Python quiz #5
 * Day 5 coding challenges


 * Resources
 * go here

Week 6: May 2
Day 6 plan


 * Class schedule
 * Day 6 lecture - working with text
 * Jupyter notebooks 2
 * basic regular expressions
 * graphing data with MatPlotLib


 * Exercises
 * counting mentions and welcomes in the Teahouse corpus
 * plotting trends over time in the Teahouse corpus


 * Homework
 * Day 6 coding challenges


 * Resources
 * go here

Week 7: May 9
Day 7 plan


 * Assignments due
 * DS4UX_(Spring_2016)#Final_Project_Proposal


 * Class schedule
 * Day 7 lecture - describing data with statistics
 * Jupyter notebooks 3
 * running statistics with SciPy


 * Exercises
 * plotting Burke-Gilman bike traffic on rainy days


 * Coding challenges
 * Day 7 coding challenges


 * Resources
 * go here

Week 8: May 16
Day 8 plan


 * Class schedule
 * Day 8 lecture - research study design


 * Exercises
 * Replicate Teahouse invite A/B test


 * Coding challenges
 * Day 8 coding challenges


 * Resources
 * go here

Week 9: May 23
Day 9 plan


 * Class schedule
 * Day 9 lecture - communicating your findings
 * review of key concepts and tools
 * presentation practice


 * Homework
 * goes here


 * Resources
 * go here

Week 10: May 30

 * Assignments due
 * Final project presentation


 * Class schedule
 * Day 10 lecture - Final project report review, next steps for Data Science
 * Final project presentations

Week 11: June 6

 * Assignments due
 * Final project report and code due by midnight on Wednesday, 6/8/2016


 * Class schedule
 * Finals week - No class!