DS4UX (Spring 2016)/Schedule

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Week 1: March 28[edit]

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
Resources



Week 2: April 4[edit]

Day 2 plan

Agenda
Homework
Resources



Week 3: April 11[edit]

Day 3 plan

Agenda
Homework
Resources
  • go here



Week 4: April 18[edit]

Day 4 plan

Agenda
Homework
Resources
  • Two video lectures by Mako Hill, which covers most of the concepts from NEXT week's lecture (as well as some useful review):



Week 5: April 25[edit]

Day 5 plan

Assignments due
Agenda
Homework
Resources



Week 6: May 2[edit]

Day 6 plan

Assignments due
Agenda
  • An interactive lecture introducing the concept of user-defined functions
Homework
Resources



Week 7: May 9[edit]

Day 7 plan

Assignments due
Agenda
  • Week 6 coding challenge solutions - Jonathan will review the solutions to the week 6 coding challenges and answer questions
  • Writing your own functions - Ray will give a lecture and lead us through a series of interactive exercises on creating custom functions to make our code simpler, clearer, and more flexible.
  • Working with location data - Jonathan will introduce some simple techniques for aggregating and visualizing datasets that have a location component, using a corpus of Seattle building permit data.
Coding challenges



Week 8: May 16[edit]

Day 8 plan

Assignments due
Agenda
  • Jupyter notebooks: intro and setup
  • Some new concepts: try/except, sleep(), dateutil.parser, datetime.datetime
  • Functions II: walk through examples in Jupyter and terminal
Coding challenges
  • No coding challenges this week!
Resources
  • Data Science from Scratch, Joel Grus (O'Reilly)



Week 9: May 23[edit]

Day 9 plan

Agenda
  • We will review the requirements for the Final Presentation and Final Project assignments
  • We will review the course as a whole, and what we accomplished
  • We will go through 1-2 more examples of how to organize a program into functions
  • We will have an opportunity to review key Python concepts as a class
  • We will have plenty of time to ask questions about and work on final projects
Resources
Free (mostly) Python 3 tutorials and reference works



Week 10: June 3 (DATE CHANGE)[edit]

Please note that this class we will meet from 6pm to 9pm on Friday evening, rather than Monday evening, because of the Memorial Day holiday.

Assignments due
Agenda
  • Final project presentations
Resources
  • one



Week 11: June 6[edit]

FINALS WEEK - NO CLASS

Assignments due