DS4UX (Spring 2016)/Schedule: Difference between revisions

From CommunityData
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;Agenda
;Agenda
*Jupyter notebooks: intro and setup
*Jupyter notebooks: intro and setup
:*[https://paws-public.wmflabs.org/paws-public/User:Jtmorgan/DS4UX%20Jupyter%20intro.ipynb Jupyter intro notebook]
:* [https://en.wikipedia.org/w/index.php?title=Special:UserLogin&type=signup CLICK HERE to create a Wikipedia account]
:* [https://paws-public.wmflabs.org/paws-public/User:Jtmorgan/DS4UX%20Jupyter%20intro.ipynb Jupyter intro notebook]
*Some new concepts: <code>try/except, sleep(), dateutil.parser, datetime.datetime</code>
*Some new concepts: <code>try/except, sleep(), dateutil.parser, datetime.datetime</code>
:*[https://paws-public.wmflabs.org/paws-public/User:Jtmorgan/Week%208%20new%20concepts.ipynb Week 8 new concepts notebook]
:* [https://paws-public.wmflabs.org/paws-public/User:Jtmorgan/Week%208%20new%20concepts.ipynb Week 8 new concepts notebook]
*Functions II: walk through examples in Jupyter and terminal
*Functions II: walk through examples in Jupyter and terminal
:* [https://paws-public.wmflabs.org/paws-public/user/Jtmorgan/notebooks/Parsing%20permit%20data%20demo.ipynb Building permit notebook]
:* [https://paws-public.wmflabs.org/paws-public/user/Jtmorgan/notebooks/Parsing%20permit%20data%20demo.ipynb Building permit notebook]

Revision as of 21:25, 16 May 2016

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
Resources



Week 2: April 4

Day 2 plan

Agenda
Homework
Resources



Week 3: April 11

Day 3 plan

Agenda
Homework
Resources
  • go here



Week 4: April 18

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

Day 5 plan

Assignments due
Agenda
Homework
Resources



Week 6: May 2

Day 6 plan

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



Week 7: May 9

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

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
  • go here



Week 9: May 23

Day 9 plan

Agenda
  • Day 9 lecture
  • review of key concepts and tools from this course
  • presentation workshop
Resources
  • go here



Week 10: June 3 (DATE CHANGE)

Please note that this class we will meet Friday evening, rather than Monday evening, because of the Memorial Day holiday.

Assignments due
Agenda
  • Day 10 lecture - Final project report review, next steps for Data Science
  • Final project presentations
Resources
  • one



Week 11: June 6

FINALS WEEK - NO CLASS

Assignments due