DS4UX (Spring 2016)/Schedule: Difference between revisions

From CommunityData
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;Agenda
;Agenda
* We'll walk through the concepts and solutions to the [[DS4UX_(Spring_2016)/Day_3_coding_challenge|code challenges]] from last week as a group.
* [[DS4UX_(Spring_2016)/Day_3_coding_challenge|Week 3 code challenges]] — We'll briefly walk through the concepts and solutions to the Week 3 coding challenges as a group.
*[[DS4UX_(Spring_2016)/Day_4_lecture|Interactive lecture]] - background of web APIs; requesting web pages with <code>requests</code>, JSON, and writing to files.
* [[DS4UX_(Spring_2016)/Day_3_follow_up|Day 3 follow up]] — We will cover some important concepts that we didn't have a chance to cover in depth last week.
* We'll discuss the Final Project Idea assignment (due next week!)
* [[DS4UX_(Spring_2016)/Wikipedia Notifications survey]] — We will walk through a real life example that uses the concepts we've developed so far to answer research questions.
* We'll begin working on [[Community Data Science Course (Spring 2015)/Wikipedia API projects|a series of projects using the Wikipedia API]].
* [[DS4UX_(Spring_2016)/Day_4_lecture|Reading and writing files]] — we will learn how to read and write basic datafiles with Python.
* [[DS4UX_(Spring_2016)/Seattle_traffic|Burke-Gilman traffic counter]] — we will start working with a dataset of bike and pedestrian traffic on the Burke-Gilman trail.
 


;Homework
;Homework
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;Resources
;Resources
* [[DS4UX_(Spring_2016)/Day_3_follow_up|Day 3 follow up]] — quick cheat sheet for some important concepts that we didn't cover in depth last week.
*  Two video lectures by Mako Hill, which covers most of the concepts from NEXT week's lecture (as well as some useful review):
*  Two video lecturs by Mako Hill, which covers most of the concepts from this week's lecture (as well as some useful review):
:* [https://communitydata.cc/~mako/cdsw-au2015-lecture2-20151024.ogv cdsw-au2015-lecture2-20151024.ogv]
:* [https://communitydata.cc/~mako/cdsw-au2015-lecture2-20151024.ogv cdsw-au2015-lecture2-20151024.ogv]
:* [https://communitydata.cc/~mako/cdsw-au2015-lecture3-20151107.ogv cdsw-au2015-lecture3-20151107.ogv]
:* [https://communitydata.cc/~mako/cdsw-au2015-lecture3-20151107.ogv cdsw-au2015-lecture3-20151107.ogv]

Revision as of 01:21, 18 April 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
  • Day 5 lecture - visualizing web data
  • Introduction to Jupyter notebooks
  • graphing data with matplotlib
Homework
Resources
  • go here

Week 6: May 2

Day 6 plan

Assignments due
  • Day 5 coding challenge


Agenda
Homework
Resources
  • go here

Week 7: May 9

Day 7 plan

Assignments due
Agenda
Coding challenges
Resources
  • go here

Week 8: May 16

Day 8 plan

Agenda
Coding challenges
Resources
  • go here


Week 9: May 23

Day 9 plan

Agenda
  • Day 9 lecture - research study design
  • 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

Week 11: June 6

FINALS WEEK - NO CLASS

Assignments due